lifetime performance assessment of thermal...

Lifetime Performance Assessment of

Thermal SystemsStudies on Building, Solar and District Heating Applications

B o j a n S to j a n o v i c

Doctoral thesis in civil and architectural Engineering

Stockholm, Sweden 2009

www.kth.se

ISBN 978-91-7415-384-2

ic Lifetime Perform

ance assessment of therm

al Systems

KtH 2009

Lifetime Performance Assessment of Thermal Systems

Studies on Building, Solar and District Heating Applications

Lifetime Performance Assessment of Thermal Systems

Studies on Building, Solar and District Heating Applications

Bojan Stojanović

Doctoral Thesis

in the subject area of

Civil and Architectural Engineering

specialised in

Building Materials Technology

September 2009

Gävle

KTH research school - University of Gävle Centre for Built Environment Building Materials Technology

KTH research school Centre for Built Environment Building Materials Technology University of Gävle SE-801 76 Gävle Sweden ISBN 978-91-7415-384-2 Printed in Sweden by Universitetsservice US-AB Stockholm © 2009 Bojan Stojanović

“A clever person solves a problem. A wise person avoids it.” Einstein, Albert (1879-1955)

PREFACE This thesis is a result of a part-time work that continued for about 5 years at the KTH research school, Centre for Built Environment - University of Gävle. I began my undergraduate studies in the field of energy technologies in the year 1999 at the University of Gävle. After about 3.5 years of studying it was time to perform and write my degree thesis. After being inspired by my teachers (today my fellow colleagues) during the studying years, I decided to perform and write my thesis with tendencies towards the Research and Development (R&D) side of energy technologies. After finishing my degree thesis at the Centre for Built Environment and attaining my degree in Bachelor of Science, I got an offer by Professor Christer Sjöström to become a PhD-student and conduct R&D on lifetime performance of thermal systems; in association to the EU project ENDOHOUSING. After some reconsideration I decided to embrace this offer and started my work, which has resulted in this Doctoral thesis. I would like to express my gratitude by thanking Professor Christer Sjöström, for giving me this opportunity to become a PhD-student and conduct R&D on this intriguing topic. I would also like to express my sincere gratitude to Dr. Jan Akander for being an excellent supervisor, mentor and colleague. Your profound knowledge and innovativeness in: building physics, thermal modelling and energy technology, has truly been instructive during these years. Furthermore, I thank Professor Ove Söderström at KTH, my colleagues at the Building Materials Technology group and the rest of the Centre for Built Environment and Department of Technology and Built Environment - University of Gävle, for helping my work. Finally, I express my gratitude to Dr. Daniel Hallberg, for sharing my time as a PhD-student with instructive discussions and co-authoring within the research area and large quantities of laughter and companionship. On the more private level, I would like to express my dearly gratitude to my parents for supporting me all the way. Furthermore, I express my gratitude’s to the Ek-Karlsson, Hagelin and Walldén family, for showing sympathy towards me and my work. Last but definitely not least, I am ‘ones again’ without words but I will try to express my gratitude to Ms. Cecilia Ek. Thank you for understanding, supporting and aiding me during all these years. Your underlying role in this work is something that is acknowledged and will not be forgotten. Thank You! For those that I have not acknowledged and thanked, you were probably not worth mentioning . The End! Gävle, April 2009 Bojan Stojanović

ABSTRACT The main questions today concerning thermal systems are their economical and environmental impacts. These entities are generally, at present, assessed on the basis of operation performances of newly installed/designed systems, during an assumed lifetime period. While this is the common way of perceiving thermal systems, performance-over-time will change as an effect of degradation, and not solely of different operation scenarios. How and to what extent is the question that needs assessing in order to evaluate if these changes will jeopardise the intended system performance requirement, hence service life (SL). The lack of knowledge/approaches and tools for assessing durability and performance-over-time of thermal systems complicates the task of incorporating these aspects in engineering. In turn, this pro-active assessment and analysis is in line with today’s performance based directives, laws and regulations; of which the working life is an essential part. The durability of materials, components and systems is not a topic that is an end in itself, but becomes a vital part in a comprehensive perspective as sustainability. The lifetime performance assessment of thermal systems, as presented in this thesis, shows that it is a vital part of the R&D in the quest of sustainable energy/thermal systems and energy use. This thesis gives knowledge to the thermal (energy) system/technology R&D and engineering sector, regarding durability and lifetime performance assessment methodologies; but also to the durability of construction works sector, regarding the needs for assessing lifetime performance of materials and components in relation to system performance. It also presents descriptions of requirements on construction works. Specifically, the studies presented in the thesis show how durability and lifetime performance assessment of thermal systems may be sought, with knowledge on: methodologies, exposure test set-ups, modelling and the attainment and use of adequate tools. The main focus is on performance-over-time modelling, tying material/component degradation to altered thermal performance, thereby attaining performance-over-time assessment tools to be used in order to incorporate these aspects when engineering thermal systems; hence enabling the forecasting of SL. The presented work was predominantly done in association to the EU project ENDOHOUSING. The project developed a solar-assisted heat pump system solution, with heat storage, to provide the thermal energy to meet space heating, cooling and hot water requirements for domestic houses in different regions of the EU. The project constituted the platform for the work presented in this thesis, thereby outlining the main context with studies on durability and lifetime performance of: flat plate solar collectors ground heat sources/storages and interaction with a heat pump system evaluation of the ENDOHOUSING solar-assisted heat pump system

The thesis also presents a study of SL prediction and estimation of district heating distribution networks (an additional thermal system application). In this particular context, the Factor Method is proposed as a methodology. The main issue of lifetime performance of thermal systems is how and to what extent performance reduction in individual materials or components influence the overall system performance, as the essence of energy/thermal system sustainability is system performance. Keywords: Lifetime performance, degradation, assessment, modelling, field exposure, thermal components and system.

LIST AND SUMMARY OF PAPERS This Doctoral thesis is based on the following appended papers, on the topic of lifetime performance assessment of thermal systems. The work and action input performed by the author of this thesis is listed within each paper description, in the case there are co-authors. PAPER I Stojanović, B. (2005). On Reduced Energy Performance of a Solar-Assisted Heat Pump System due to Absorber Coating Degradation. Proceedings of the 10th International Conference on Durability of Building Materials and Components (10DBMC), Lyon, France. The paper presents a literature study of the degradation of flat plate solar collectors used in Domestic Hot Water (DHW) systems. The scope of the paper is limited to the selective absorber coating of the collector and is focused on the research made in the IEA Task X study. The objective is to investigate the potentials of computer simulations of performance reduction in solar-assisted heat pump systems, due to absorber coating degradation. PAPER II Stojanović. B., Akander, J. (2005). Long-Term Thermal Performance Modelling and Simulations of a Borehole. Proceedings of the 7th Symposium on Building Physics in the Nordic Countries, Reykjavik, Iceland. The paper presents the long-term thermal performance modelling and simulation of a single heat extraction borehole equipped with a U-shaped pipe, by applying the Macro Element Modelling (MEM) method developed by D. Schmidt in 2004. The advantage of this modelling method is that it establishes a simplified yet accurate thermal borehole model, which requires less computing time and power compared to a traditional finite difference/element model. This simplifies the task of performing several decades of long-term thermal performance simulations. Work input: Main writer, literature review, modelling implementation under supervision. PAPER III Stojanović, B., Akander. J., Eriksson, B. (2008). Natural and Semi-Natural Field Exposure Testing and Analysis, on Optical Degradation of a Building Integrated Unglazed Solar Collector Surface. Materials and Structures. 41, 1057-1071. The paper presents a study on optical degradation of a building integrated Unglazed Solar Collector (USC) surface, by exposing USC specimens to a natural and semi-natural field exposure test. Particular interest is devoted to the semi-natural field exposure test method evaluation and the degradation of optical properties. The semi-natural field exposure test consisted of cooling USC specimens with a Direct-Air Peltier Element in order to increase the Time of Wetness (TOW), hence to ‘simulate’ an active cooling of the component, as is the

case for USC’s, and to assess the role of TOW on optical degradation of the USC. The TOW was estimated through measurements with WETCORR sensors (monitoring surface temperatures and moisture) and climate parameters (temperature and relative humidity) at site. Work input: Main writer, literature review, experimental set-up of specimens and test rigs, monitoring, use of analysis instruments, data analysis and interpretation. PAPER IV Stojanović. B., Akander, J. (2008). Use of a Peltier Element to Increase Time of Wetness of Unglazed Solar Collector Specimens in a Natural Field Exposure Test. Proceedings of the 11th International Conference on Durability of Building Materials and Components (11DBMC), Istanbul, Turkey. This paper is a continuation of Paper III, which focuses on evaluating the prolonged field exposure of the Unglazed Solar Collector (USC) specimens. The paper primarily focuses on the semi-natural field exposure test set-up and the increase of Time of Wetness (TOW). After about two years of exposure, at this particular test site in Gävle Sweden, the TOW was more than doubled in comparison to non-cooled specimen surfaces. The Peltier Element proved to be inexpensive and flexible for this purpose. Work input: Main writer, experimental set-up of specimens and test rigs, monitoring, data analysis and interpretation. PAPER V Akander. J., Stojanović. B., Hallberg, D. (2008). Simulated Long-Term Thermal Performance of a Building That Utilizes a Heat Pump System and Borehole. Proceedings of the 11th International Conference on Durability of Building Materials and Components (11DBMC), Istanbul, Turkey. This paper is a continuation of Paper II. The paper serves to quantify the long-term thermal performance degradation of a component, in this case the borehole, and how the degradation of this component affects the performance-over-time of an entire heat pump system, in this case the heating system of the building. The building, which the heat pump serves, is assumed to be a typical Swedish house with normal energy consumption. Simulation results show that the depth of the borehole is of great importance to limit over-time temperature drops. The efficiency of the heat pump system is directly dependent of temperatures in the borehole. Work input: Refined borehole modelling and involved in energy system result analysis.

PAPER VI Hallberg, D., Akander, J., Stojanović, B., Kedbäck, M. (2008). Life cycle Management System - A Planning Tool Supporting Long-Term Based Design and Maintenance Planning. Proceedings of the 11th International Conference on Durability of Building Materials and Components (11DBMC), Istanbul, Turkey. This paper presents two case studies within the project Bygga Villa, which has developed a web-portal tool for Service Life (SL) and maintenance intervals estimates, of different building parts and systems, based on environmental-dependent degradation models. The project, hence the tool, is specifically focused on residential houses. The first case focuses on SL performance analysis of exterior parts of buildings. The second focuses on SL performance analysis of energy systems; here specifically a borehole assisted heat pump heating system. Work input: Refined borehole modelling and energy system result analysis. PAPER VII Stojanović, B., Hallberg, D., Akander, J. (2008). A Steady State Thermal Duct Model Derived by Fin-Theory Approach and Applied on an Unglazed Solar Collector. Submitted to the journal Solar Energy in November 2008; status: under review. This paper presents the thermal modelling of an Unglazed Solar Collector (USC) flat panel, with the aim of attaining a detailed yet swift thermal steady-state model. The model is analytical, one-dimensional (1-D) and derived by a fin-theory approach. The derived model is meant to be used for efficient optimisation and design of USC flat panels (or similar applications), as well as detailed thermal analysis of temperature fields and heat transfer distributions/variations at steady-state conditions; without requiring a large amount of computational power and time. Detailed surface temperatures are necessary features for durability studies of the surface coating, hence the effect of coating degradation on USC and system performance. The model accuracy and proficiency has been benchmarked against a detailed three-dimensional Finite Difference Model (3-D FDM) and two simpler 1-D analytical models. Results from the benchmarking test show that the fin-theory model has excellent capabilities of calculating energy performances and fluid temperature profiles, as well as detailed material temperature fields and heat transfer distributions/variations (at steady-state conditions). Work input: Main writer, literature review, co-worker on solving the analytical model, implementation of the analytical solution into numerical code, analysis and compilation of results. PAPER VIII Hallberg, D., Stojanović, B., Akander, J. (2009). Status, Needs and Possibilities for Service Life Prediction and Estimation of District Heating Distribution Networks. Submitted to the journal Structure and Infrastructure Engineering - Maintenance, Management, Life-Cycle Design & Performance, in January 2009; status: accepted.

The implementation of an optimised and proactive maintenance strategy, in the context of District Heating (DH), requires efforts and abilities for predicting future performances and estimating Service Life (SL) of DH components. A literature review on failures (damages and performance reductions) occurring on DH pipes, reveals that failures in DH pipes are mainly leaks due to corrosion or mechanical impacts and reduced thermal insulation performance. A feasible SL estimation method for DH pipe leakage is the Factor Method. Since the application of this method within the context of DH pipes has not been found in other publications, this paper focuses on describing the method and discusses the possibilities on how to apply it in two specific cases with respect to leakage: SL estimation of repaired DH pipe sections (i.e. maintenance of DH network) and of DH pipes in new or extended DH networks. A particular attention is paid on which modifying factors to consider and how to quantify them. Work input: Co-writer, co-worker on discussing and analysing the application and use of the suggested SL estimation method. PAPER IX Stojanović, B., Akander. J. (2009). Build-Up and Long-Term Performance Test of a Full-Scale Solar-Assisted Heat Pump System for Residential Heating in Nordic Climatic Conditions. Submitted to the journal Applied Thermal Engineering in February 2009; status: under review. This paper presents the build-up and long-term performance test of a full-scale Solar-Assisted Heat Pump System (SAHPS) for residential heating in Nordic climatic conditions. This particular SAHPS was developed within the EU project ENDOHOUSING. The analysis primarily focuses on system performance, with emphasis on Heat Pump (HP) and total system Seasonal Performance Factor (SPF). Analysis shows that despite unfavourable building conditions, for low energy use and utilisation of a SAHPS, the system was successfully in full operation (for about two years) fulfilling heating requirements. The system displayed a HP and total SAHPS performance of: SPFHP=2.85 and SPFSAHPS=2.09. The authors argue that with an optimised SAHPS control and operation strategy, additional use of circulation pumps and auxiliary energy (electricity) could be vastly reduced, hence attaining a SPFSAHPS value that is equivalent to the SPFHP. As the Nordic (Swedish) ENDOHOUSING SAHPS has not yet been properly optimised/designed and installed in an appropriate house, the SPFHP=2.85 is considered as being a success. Work input: Main writer, involved in system solution refinement, monitoring set-up, monitoring campaign, data handling and data analysis, thermal performance evaluation.

TABLE OF CONTENTS

PREFACE ................................................................................................................... I

ABSTRACT............................................................................................................... III

LIST AND SUMMARY OF PAPERS.......................................................................... V

TABLE OF CONTENTS............................................................................................ IX

LIST OF SYMBOLS .................................................................................................. XI

LIST OF ABBREVIATIONS .....................................................................................XV

1 INTRODUCTION................................................................................................. 1

1.1 THE EUROPEAN CONSTRUCTION PRODUCTS DIRECTIVE........................................... 1 1.2 THE EUROPEAN ENERGY PERFORMANCE OF BUILDINGS DIRECTIVE ...................... 2 1.3 REMARKS.............................................................................................................................. 2 1.4 SCOPE AND OBJECTIVES................................................................................................... 3

1.4.1 Scope................................................................................................................................. 3 1.4.2 Objectives .......................................................................................................................... 4

2 DURABILITY AND SERVICE LIFE ASSESSMENT METHODOLOGIES .......... 5

2.1 ENVIRONMENTAL CHARACTERISATION, CLASSIFICATION AND MAPPING................ 7 2.2 MATERIAL AND COMPONENT TESTING ........................................................................... 8

2.2.1 Long-term field and in-use exposure ................................................................................. 9 2.2.2 Short-term accelerated and in-use-condition exposure................................................... 10 2.2.3 Examples of some test procedures for thermal systems................................................. 11

2.3 METHODS AND APPROACHES FOR SERVICE LIFE PREDICTION MODELLING......... 11 2.3.1 Physicochemical and empirical modelling ....................................................................... 11 2.3.2 Probabilistic and deterministic modelling......................................................................... 13 2.3.3 Mathematical methods of statistical modelling ................................................................ 16

2.4 DOSE-RESPONSE AND DAMAGE FUNCTIONS .............................................................. 19 2.5 PERFORMANCE-OVER-TIME............................................................................................ 22 2.6 THE ARRHENIUS EQUATION............................................................................................ 24 2.7 THE FACTOR METHOD...................................................................................................... 25 2.8 LIFE CYCLE MANAGEMENT SYSTEM.............................................................................. 27 2.9 REMARKS............................................................................................................................ 29

3 GENERAL DESCRIPTION ON SOLAR ENERGY, HEAT PUMPS AND SOLAR-ASSISTED HEAT PUMPS ....................................................................................... 33

3.1 GLAZED AND UNGLAZED FLAT PLATE SOLAR COLLECTORS .................................... 33 3.2 THE HEAT PUMP SYSTEM ................................................................................................ 36

3.2.1 Commonly used heat sources ......................................................................................... 38 3.2.2 The temperature dependence of heat pump COP .......................................................... 39

3.3 SOLAR-ASSISTED HEAT PUMP SYSTEM........................................................................ 42

4 GENERAL DESCRIPTION ON DURABILITY OF THERMAL SYSTEMS........ 45

4.1 SOLAR COLLECTORS AND HEAT PUMPS UTILISED IN BUILDINGS............................ 45

5 THE EU PROJECT ENDOHOUSING ............................................................... 49

5.1 THE SWEDISH DEMONSTRATION SITE .......................................................................... 52 5.2 SYSTEM PERFORMANCE EVALUATION METHODOLOGY............................................ 56 5.3 LONG-TERM SYSTEM PERFORMANCE RESULTS......................................................... 57

6 LONG-TERM THERMAL PERFORMANCE MODELLING OF A BOREHOLE 61

6.1 THE BOREHOLE MODEL ................................................................................................... 65 6.2 BOREHOLE COUPLED HEAT PUMP SYSTEM PERFORMANCE MODEL...................... 71

7 OPTICAL DEGRADATION OF A BUILDING INTEGRATED UNGLAZED SOLAR COLLECTOR SURFACE ........................................................................... 73

7.1 THE FIELD TEST SET-UP EXPOSURE ............................................................................. 74 7.2 LOCAL AND MICROCLIMATE MONITORING.................................................................... 76 7.3 OPTICAL SURFACE DEGRADATION ................................................................................ 78

8 THERMAL FLAT PANEL COLLECTOR MODEL ............................................ 81

8.1 FIN-THEORY BASED USC THERMAL DUCT MODEL ...................................................... 82 8.2 MATHEMATICAL DERIVATION.......................................................................................... 83 8.3 CALCULATION RESULTS .................................................................................................. 85

9 SERVICE LIFE PREDICTION OF DISTRICT HEATING DISTRIBUTION NETWORKS............................................................................................................. 89

9.1 FAILURE CHARACTERISTIC OF DISTRICT HEATING PIPES......................................... 90 9.2 THE APPLICATION OF THE FACTOR METHOD .............................................................. 91

10 SUMMARY OF RESULTS WITHIN THE STUDIES.......................................... 93

11 DISCUSSION AND CONCLUSIONS................................................................ 97

12 FUTURE WORK ..............................................................................................101

REFERENCES ........................................................................................................103

ON REDUCED ENERGY PERFORMANCE OF A SOLAR-ASSISTED HEAT PUMP SYSTEM DUE TO ABSORBER COATING DEGRADATION ......................................................................................... I

LONG-TERM THERMAL PERFORMANCE MODELLING AND SIMULATIONS OF A BOREHOLE .. II

NATURAL AND SEMI-NATURAL FIELD EXPOSURE TESTING AND ANALYSIS, ON OPTICAL DEGRADATION OF A BUILDING INTEGRATED UNGLAZED SOLAR COLLECTOR SURFACE ... III

USE OF A PELTIER ELEMENT TO INCREASE TIME OF WETNESS OF UNGLAZED SOLAR COLLECTOR SPECIMENS IN A NATURAL FIELD EXPOSURE TEST ............................................. IV

SIMULATED LONG-TERM THERMAL PERFORMANCE OF A BUILDING THAT UTILIZES A HEAT PUMP SYSTEM AND BOREHOLE ........................................................................................................V

LIFE CYCLE MANAGEMENT SYSTEM - A PLANNING TOOL SUPPORTING LONG-TERM BASED DESIGN AND MAINTENANCE PLANNING .........................................................................................VI

A STEADY STATE THERMAL DUCT MODEL DERIVED BY FIN-THEORY APPROACH AND APPLIED ON AN UNGLAZED SOLAR COLLECTOR ........................................................................VII

STATUS, NEEDS AND POSSIBILITIES FOR SERVICE LIFE PREDICTION AND ESTIMATION OF DISTRICT HEATING DISTRIBUTION NETWORKS...........................................................................VIII

BUILD-UP AND LONG-TERM PERFORMANCE TEST OF A FULL-SCALE SOLAR-ASSISTED HEAT PUMP SYSTEM FOR RESIDENTIAL HEATING IN NORDIC CLIMATIC CONDITIONS.......... IX

LIST OF SYMBOLS List of major symbols used within the thesis. Others are defined as they first appear in the text. a thermal diffusivity (m2/s) A matrix transformation parameter (-) Ac solar collector area (m2) b fin thickness (m) B matrix transformation parameter (K/W) c power series parameter (-) c1 heat loss coefficient at (Tm-Ta)=0 (W/m2 K2) c2 temperature dependence of heat loss coefficient (W/m2K) c3 wind speed dependence of heat loss coefficient (J/m3K) c4 sky temperature dependence of heat loss coefficient (W/m2K) c5 effective thermal capacity (J/m2K) c6 wind speed dependence of the zero heat loss efficiency (s/m) C heat capacity (kJ/kgK) C RC-network heat capacity (kJ/K) C matrix transformation parameter (W/K) C equation constant (unit) C[Tf(z)] equation constant as a function of fluid temperature (unit) cp specific heat capacity (J/kgK) COP coefficient of performance (-) D matrix transformation parameter (-) E electrical energy (J) E electrical power (W) ET activation energy (kJ/mol) EL long-wave irradiance (W/m2) f function (unit) FR collector heat removal factor (-) F´(τα)en zero loss efficiency (-) G solar irradiance (W/m2)

i imaginary number ( 1 ) Im imaginary part (-) Kθ(θ) incident angle modifier (-) Kθb(θ) incident angle modifier for beam irradiance (-) Kθd incident angle modifier for diffuse irradiance (-) l length (m) L load (unit) L fin length (m) L(x) load density function probability (-) m mass flow (kg/s) P probability (-) Pfailure failure probability (-) Pfailure, SL probability of failure within a SL distribution (-) Ptarget maximum amount of accepted failure probability (-) P(t) cumulative density function probability (-)

q[x, Tf(z)] heat flux in an infinite small fin element as a function of (W/m2) position in a fin and fluid temperature Q heat-transfer rate (W) Q[x, Tf(z)] heat transfer rate in an infinite small fin element as a function of (W) position in a fin and fluid temperature Q[Tf(z)] heat transfer rate as a function of fluid temperature (W/m) Q~ fluctuating heat-transfer rate (W) Q thermal energy (J) real real part (-) R ideal gas constant (kJ/K mol) R RC-network thermal resistance (K/W) R load resistance (unit) R(x) load resistance density function probability (-) S effective total solar irradiance (absorbed by the plate) (W/m2) SL(t) service life density function probability (-) t time (s) T temperature (K) T~

fluctuating temperature (K)

T̂ non fluctuating temperature (K) TD transmittance (W/K) Teff effective mean-temperature (K) Tif inlet fluid temperature (K) Tm mean-solar collector temperature (K) Tmf mean-fluid temperature (K) TR reference temperature (K) T(z) temperature as a function of USC duct length position (K) T(in) inlet temperature (K) T[x, Tf(z)] temperature as a function of position in a fin and fluid temperature (K) u ambient air speed (m/s) UL total heat loss coefficient (W/m2K) V ambient air speed (m/s) x Cartesian coordinate parameter (-) y Cartesian coordinate parameter (-) y degradation time (time) yR reference degradation time (time) ys in-service degradation time (time) Y admittance (W/K) z Cartesian coordinate parameter (-) GREEK LETTERS solar absorptance (0.3 – 2.5 μm) (-) S weighted solar absorptance (-) difference (-) IR emittance (2.5 – ~50 μm) (-) Carnot modifying efficiency factor (-) thermal conductivity (W/mK) wavelength (μm)

ρ density (kg/m3) ρ reflectance (-) σ Stefan-Boltzmann constant (W/m2K4) time fraction of one year (-) Φ(x) cumulative density function probability (-) (x) density function probability (-) cycle frequency (1/s) SUBSCRIPTS a ambient AH Auxiliary Heat b backside b beam Bh Borehole comp compressor cond condenser CP Circulation Pump d diffuse DCW Domestic Cold Water DHW Domestic Hot Water evap evaporator ext extracted f fluid fin fin g global GHE Ground Heat Exchanger HP Heat Pump HS Hot Store in in n number of step Norm Normalised out out r radiation s surface sky sky SAHPS Solar-Assisted Heat Pump System SH Space Heating SH or DHW Space Heating or Domestic Hot Water tot total trad traditional USC Unglazed Solar Collector from to

LIST OF ABBREVIATIONS 1-D One-Dimensional 2-D Two-Dimensional AH Auxiliary Heat BBR Boverkets Bygg Regler BHE Borehole Heat Exchanger CFD Computational Fluid Dynamics COP Coefficient of Performance CP Circulation Pump CPD European Construction Products Directive DH District Heating DHW Domestic Hot Water EDX Energy Dispersive X-ray Spectroscopy EPBD European Energy Performance of Buildings Directive ESLC Estimated Service Life of a Component or Assembly EU The European Union FEM Finite Element Method FMEA Failure Modes and Effects Analysis FTIR Fourier Transform Infrared Spectroscopy GHE Ground Heat Exchanger HP Heat Pump IEA International Energy Agency IR Infrared ISO International Organization for Standardization LCC Life Cycle Cost LCE Life Cycle Ecology LMS Life Cycle Management System MLE Maximum Likelihood Estimation MR&R Maintenance Repair and Refurbishment PE Peltier Element PV Photovoltaic PV/T Photovoltaic/Thermal R&D Research and Development RSL Reference Service Life RSLC Reference Service Life of a Component or Assembly RSLP Reliability based Service Life Prediction SAHPS Solar-Assisted Heat Pump System SEM Scanning Electron Microscopy SL Service Life SLPA Service Life Prediction Analysis SPF Seasonal Performance Factor TOW Time of Wetness USC Unglazed Solar Collector UV Ultraviolet UV/VIS/NIR Ultraviolet/Visible/Near Infrared Spectroscopy

1 INTRODUCTION At a first glance, construction works (EC, 1988) and their materials, components and systems may be perceived as static objects. Durability and lifetime performance dynamics is often not reflected upon, mostly due to slow course of events and vast time spans. This perception often prevails in the building sector regarding energy/thermal technologies/systems and their long-term performance. When installing a thermal system (e.g. for heating or cooling) in a building, its performance and efficiency is mostly seen as static over time; only changing as a result of different operation scenarios. While this is the common perception, changes in system performance-over-time will likely occur due to e.g. some material degradation, which alters system efficiency. How and to what extent, is the question that needs assessing in order to evaluate if these changes will jeopardise the intended system performance requirement. In turn, this pro-active assessment and analysis is in line with the European Directives: the European Construction Products Directive (CPD) and the European Energy Performance of Buildings Directive (EPBD); regarding all building products and energy performance, in the quest of sustainable development in the built environment. 1.1 THE EUROPEAN CONSTRUCTION PRODUCTS DIRECTIVE A common platform for building product codes, regulations and standards was set forth by the European Union (EU) council in December 1988. Its purpose is to harmonise the market of building materials, products and systems; in order to prevent trade barriers between counties within the EU and support sustainable development. According to the European Construction Products Directive (CPD) (EC, 1988); all building materials, products or systems must meet six major requirements:

1. Mechanical resistance and stability 2. Safety in case of fire 3. Hygiene, health and the environment 4. Safety in use 5. Protection against noise 6. Energy economy and heat retention

These essential requirements on construction works should be met during the intended working life of the building. The definition of working life according to the CPD interpretive documents paragraph 1.3 (EC, 2002, a), is: “The working life is the period of time during which the performance of the works will be maintained at a level compatible with the fulfilment of the essential requirements” This results, in essence, in a performance requirement on all building products. The lifetime performance of building materials, products and systems has to be assessed and declared.

1.2 THE EUROPEAN ENERGY PERFORMANCE OF BUILDINGS DIRECTIVE The European Energy Performance of Buildings Directive (EPBD) (EC, 2002, b) was published in the official journal in January 2003. The overall objective of the directive is to promote the improvement of energy performance of buildings within the EU community, taking into account outdoor climatic and local conditions; as well as indoor climate requirements and cost-effectiveness. Each EU member state was required to transpose the directive into law by the beginning of 2006, with a further three years being allowed for full implementation of specific articles. The EPBD contains four main requirements:

1. A common methodology for calculating the integrated energy performance of buildings.

2. Minimum standards on the energy performance of new buildings and existing buildings that are subjected to major renovation.

3. Systems for the energy certification of new and existing buildings, and (for public buildings) prominent display of this certification and other relevant information. Certificates must be less than five years old.

4. Regular inspection of boilers and central air-conditioning systems in buildings and in addition, an assessment of heating installations in which the boilers are more than 15 years old.

The law of energy declaration of buildings came into effect October 2006 in Sweden. The purpose of the law is to implement the EPBD into Swedish legislation and thereby promote an efficient energy use and a good indoor environment in buildings. The Swedish National Board of Housing, Building and Planning (Boverket), has the authorisation and has written regulations for supporting the implementation of this law. An excerpt taken from the written regulation Boverkets Bygg Regler (BBR) (Boverket, 2008) is presented here, in order to exemplify how the EPBD has been transposed down to a Swedish performance-based demand on the engineering level. “Dwellings shall be designed so that the: specific energy use (excluding electricity used for domestic appliances) and building envelope mean heat transfer coefficient of the building (regarding buildings that have non electrical heating) does not exceed the maximum amount of 130 kWh per m2 floor area and year, and Um =0.5 W/m2 (in climate zone II)” 1.3 REMARKS These directives, laws and regulations (as discussed above) clearly show how requirements on building materials, components and systems are or have emerged from traditionally being prescriptive into performance-based requirements; of which the working life is an essential part. This also lays emphasis on the design and performance of e.g. a building, to fulfil the requirements not on the basis of individual parts, but as an assembled system.

1.4 SCOPE AND OBJECTIVES Lifetime performance of thermal systems is a vast Research and Development (R&D) field encompassing a wide variety of different materials, components, system-types and combinations. The currently available lifetime performance knowledge is in general sparse, with studies on some system components or materials, making the information case-dependent and inappropriate for application in a wide context. This reflects the historical and up to date prevailing perception of thermal systems, that performance and efficiency is static over time, only changing as a result of different operation scenarios; whilst changes in system performance-over-time will likely occur due to e.g. some material degradation, which alters the system efficiency. How and to what extent, is the question that needs assessing in order to evaluate if these changes will jeopardise the intended system performance requirement, hence service life. Due to lack of knowledge/approaches and tools for assessing durability and performance-over-time complicates the task of incorporating these aspects when engineering thermal systems, hence the promotion of sustainable development. 1.4.1 Scope The presented work on lifetime performance of thermal systems was predominantly done in association to the EU project ENDOHOUSING (Endothermic Technology for Energy Efficient Housing in the EU, Project No: NNE5-2001-00565) (Virk, 2008). The project developed a solar-assisted heat pump system solution, with heat storage, to provide the thermal energy to meet space heating, cooling and hot water requirements for domestic houses in different regions of the EU throughout the year (see chapter 5). Inspiration on how to perceive lifetime performance of thermal systems/technologies has mainly been gained from the work performed on solar collector material durability in the Task X (Task 10) study (Carlsson et al., 1994); Solar Materials Research and Development, of the International Energy Agency’s (IEA) Solar Heating and Cooling programme. The ENDOHOUSING project constituted the platform for the work presented in this thesis, thereby outlining the main context with studies on durability and lifetime performance of: flat plate solar collectors ground heat sources/storages and interaction with a heat pump system evaluation of the ENDOHOUSING solar-assisted heat pump system

The only non ENDOHOUSING associated work, presented in this thesis, is the study of service life prediction and estimation of district heating distribution networks (an additional thermal system application). In this particular context, the Factor Method (ISO, 2000; ISO, 2008) is proposed as a methodology. Besides the specific studies, the thesis presents a general review of the R&D field Durability of Construction works (chapter 2 in this thesis). Its primary purpose is to present and highlight this subject to researchers, engineers and trade & industry, within the energy/thermal technology sector. The recommendation for readers is to look into the referred literature in chapter 2 if a more profound knowledge is sought.

1.4.2 Objectives Energy/thermal system performance refers to the energy use and output from the system. The prime objective of this thesis is to contribute to the sustainable development of thermal systems and energy use in buildings, by increasing awareness and presenting results and needs on lifetime performance assessments. The emphasis of the work is to tie material/component degradation to altered thermal performance; hence the attainment of performance-over-time assessment tools in order to incorporate these aspects when engineering thermal systems, thereby also enabling the forecasting of service life. Another objective is to evaluate the long-term performance of the Swedish ENDOHOUSING solar-assisted heat pump system solution. The presented work on lifetime performance of thermal systems, within the scope and context of the thesis, aims to: Give the thermal (energy) system/technology R&D and engineering sector an insight

to durability and performance-over-time assessment methodologies. This includes a presentation of knowledge/approaches, exposure test set-ups and tools for durability and performance-over-time assessments and a method for forecasting service life.

Explore the possibilities of:

- attaining appropriate thermal models for assessing the exposure of degradation agents on a micro level

- evaluating how material/component degradation alters the thermal performance of the system as a whole

- attaining performance-over-time models through adapted thermal modelling The main issue of lifetime performance of thermal systems is how and to what extent performance reduction in individual materials or components influences the overall system performance, as the essence of thermal/energy system sustainability is system performance. The regarded thermal/energy system boundary is the building and all discussions are within that context.

2 DURABILITY AND SERVICE LIFE ASSESSMENT METHODOLOGIES

In order to increase accessibility to the content of this thesis, a number of stipulative terms commonly used in this thesis (and within the R&D field Durability of Construction works) will be presented and defined. According to the ISO 15686-1 standard (ISO, 2000), the following definitions are: Service Life (SL): period of time after installation during which a building or its parts

meets or exceeds the performance requirements Performance-over-time: description of how a critical property varies with time Degradation agent: whatever acts on a building or its parts to adversely affect its

performance Degradation mechanism: chemical, mechanical or physical part of a reaction that

leads to adverse changes in a critical property of a building product Degradation: change over time in the composition, microstructure and properties of a

component or material, which reduces its performance Durability: capability of a building or its parts to perform its required function over a

specific period of time under the influence of the agents anticipated in service The performance-over-time for any construction works is in general a function that describes a specific measurable performance characteristic, in a certain service/exposure (degradation) environment and during a time period (see Fig. 1). In order to attain knowledge of the expected SL, a requirement (limit state) is applied onto the performance-over-time function. It is generally agreed that the factors affecting (degrading) the performance-over-time, hence the SL, are stochastic (Marteinsson, 2005). In reality, a performance-over-time function describes a statistical distribution of a performance property (Jernberg et al., 2004). The stochastic appearance of degradation is ‘often’ due to: multiple degradation factors and mechanisms, synergetic interactions and long-term course of events. These conditions present obstacles for having a full knowledge of the time-dependent causality concerning material or component degradation, thereby preventing the achievement of an ‘accurate’ deterministic degradation or performance-over-time function, hence SL prediction.

Fig. 1. A schematic figure of the performance-over-time for an arbitrary construction works, with an applied requirement in order to attain the expected SL. Picture source: Marteinsson (2005).

Marteinsson (2005) discusses that a hypothetical SL distribution model may be described with the function presented in Eq. 1, for a given type of material or component at a given location. t) pr(s, t), d(s, iq(s), t,ft s,SL )( (1) SL: Service life distribution function t: time s: general space coordinate (vector) iq: initial material or component quality d: degradation pr: performance requirement criteria There are a number of available SL and durability assessment methodologies for construction works, some of which are presented in this thesis. A general methodology for SL prediction of building components is given in the ISO 15686-1 and 2 standards (ISO, 2000; ISO, 2001) (see Fig. 2). In general, SL and durability of materials, components and systems should methodically be assessed in each case.

Fig. 2. Methodology for SL prediction of building materials, components and systems (ISO, 2001).

2.1 ENVIRONMENTAL CHARACTERISATION, CLASSIFICATION AND MAPPING

To establish a performance-over-time or degradation/damage function, a thorough knowledge of the degradation environment is necessary (see Fig. 3). By identifying relevant degradation agents and mechanisms (which affects the SL of a material or component) and characterising the degradation environment, gives the possibility of attaining knowledge for making SL predictions. Degradation on a material or component is an effect of an exposure environment and its prevailing degradation agents.

Fig. 3. A schematic figure representing the relation between degradation environment, material or component durability and performance (Jernberg et al., 2004). Characterisation of the degradation environment includes determination of the range and level of degradation agents, in the exposure environment. A categorisation of degradation agents affecting the SL of building materials, components and systems is presented in Table 1 (ISO, 1984). Table. 1. Degradation agents affecting the SL of building materials, components and systems (ISO, 1984). Mechanical Electromagnetic Thermal Chemical Biological Gravity Forces and imposed or restrained deformation Kinetic energy vibration and noise

Radiation Electricity Magnetism

Extreme levels or fast alterations of temperature

Water and solvents Oxidising agents Reducing agents Acids Bases Salts Chemically neutral

Vegetable and microbial Animal

Work has been done and is ongoing on geographical mapping of degradation agents and classifying material degradation, in order to facilitate durability and SL assessments of materials, components and systems. Classification of degradation is made in connection to the severity of relevant exposure environment agents. A review of various approaches and results on classifications and mappings is presented by Haagenrud (1997).

Degradation environment

Performance- over-time

Durability

Short-term exposure

Long-term exposure

Accelerated exposure

In-use-condition (no-acc) exposure

Field exposure

Inspection of buildings (systems)

Experimental buildings (systems)

In-use exposure

It is important to note that environmental characterisation, classification and mapping can be and is made on different geographical scales. One frequently used scale basis is the division into (Sjöström and Brandt, 1990): Macro: e.g. Europe / country map

Meso: e.g. urban area

Local: e.g. city block / building Micro: e.g. building component / material surface

The choice of scale has a large impact on the attained information. In order to have an overarching and widely useful characterisation, classification or mapping, description on a large scale-dimension (e.g. macro or meso) is necessary. In turn, this leads to loss of accuracy on smaller levels (local or micro), as e.g. climatic parameters and pollution may vastly vary at local or micro site levels. The microenvironment is crucial to material degradation. The proper uses of degradation/damage functions require characterisation and mapping of relevant degradation agents on the different geographical scales (Haagenrud, 1997). 2.2 MATERIAL AND COMPONENT TESTING In general, there are two main approaches for material and component durability testing, as presented in Fig. 4 (ISO, 2001); (see also Fig. 2):

Fig. 4: A figure chart of the main approaches for material and component durability testing (ISO, 2001).

Some main parts of the chart in Fig. 4 will be discussed more thoroughly in this section, namely: long-term field and in-use exposure short-term accelerated and in-use-condition exposure

2.2.1 Long-term field and in-use exposure Long-term field exposure is a way of testing the durability of materials and components, while having a controlled test set-up with relevant degradation agents under observation. This gives information of the semi-synthetic real-time durability, during the influence of agents naturally present at the exposure site/sites (natural field exposure). The reason for labelling this type of test as being partly synthetic is: the size effect (Marteinsson, 2005) and that these tests are more or less established under controlled conditions (Haagenrud, 1997). The size effect implies that small specimens (as often tested) will statistically have fewer faults than is common for larger e.g. surfaces. Small specimens are also more likely to behave as points in space rather than continuous component surfaces, e.g. experiencing different wind patterns (hence pollution), surface temperatures and moisture due to area and mass. A major task is to transform the long-term field exposure test results into in-use conditions. An example of long-term field exposure is corrosion testing of various metals, where metal test specimens are mounted on a 45 inclined rack, facing south (Henriksen, 2004). As stated by ISO 15686-2 standard (ISO, 2001) and Jernberg et al. (2004), exposing components to the ‘natural’ environment may be regarded as an accelerated exposure, e.g. using a 45° inclination towards the sun or by selecting special locations with high levels of one or more important degradation agents, e.g. UV-solar radiation regarding degradation of organic coatings. Besides ‘natural’ field exposure, a ‘semi-natural’ field exposure can be obtained if e.g. one of the stresses in the environment is increased or an additional factor is added (Jernberg et al., 2004). As an example the study by Stojanović et al. (2008) and Stojanović and Akander (2008), see Paper III and IV in the thesis, presents a semi-natural field exposure test set-up. In this study, specimens of an Unglazed Solar Collector (USC) were mounted on a direct-air peltier element, which cooled the surfaced in order to increase the Time of Wetness (TOW) (surface moisture condensation), hence ‘simulating’ an active cooling of the component, as is the case for USC’s (see also chapter 7), and to assess the role of TOW on optical surface degradation. In-use exposure is an intentional use of a component in a full-scale building, system or structure under normal use, in order to evaluate the SL of the component. The aim of the approach is to create a well-observed experimental situation, where the component is (presumably) under the influence of all degradation agents of the in-service condition. The down side of this exposure is difficulties in controlling, measuring and describing the exposure environment and its degradative effects. In-use exposure is a necessary part of the durability evaluation, especially when degradation agents and mechanisms acting on a component are directly related to user actions (Jernberg et al., 2004).

2.2.2 Short-term accelerated and in-use-condition exposure An accelerated short-term test procedure is a rapid way (in comparison to long-term testing) of attaining knowledge on change in some material or component property, which presumably also occurs in long-term or in-use exposures. The rapid property change is due to an accelerated degradation, which is an effect of increased degradation agent levels in an exposure environment (in comparison to long-term and in-use exposures). According to Jernberg et al. (2004), short-term exposures can be structured into three major groups:

1. reference components / comparative exposures

Used to rank and classify new components in reference to existing. 2. simulated and accelerated environmental exposures An attempt to simulate and accelerate the entire in-service environment, or at least the dominating degradation agents present at in-service conditions.

3. acceptance exposures

An accelerated procedure designed with a pass or fail performance criterion, which relies on experience of the performance of similar components in specific environments.

An accelerated short-term exposure should normally be designed from information obtained in pre-test or long-term exposure (see Fig. 2), of equal or similar components. It is essential to confirm that the degradation agents and mechanisms induced by accelerated short-term exposures, are the same or similar as those observed in service. A more detailed presentation of the charts in Figure 2 and 4 is given in the ISO 15686-1 and -2 standard (ISO, 2000; ISO, 2001) and by Jernberg et al. (2004). Durability testing is a complicated task. It demands laborious planning and assessment in order to attain a test set-up that properly regards degradation agents and mechanisms (in the exposure environment/environments), and has a reliable degradation measure. As discussed by Marteinsson (2005), some main difficulties of material and component durability testing can be listed as: a degradation mechanism usually depends on many factors (agents), which may affect

the process in a synergetic way, and the dominant failure mode may differ between different environments

degradation is often so slow that the time to get enough failed examples easily

becomes long, and the temporal variability of test specimens may be large accelerated testing can be difficult, as the increased agent level and limited range of

agents (in the case of laboratory testing) complicates comparison with actual in-use degradation

it can be problematic to measure the effect of degradation during testing (long-term)

According to the ISO 15686-2 standard (ISO, 2001) and Jernberg et al. (2004); short-term exposures are usually, but not always, based upon accelerated ageing. In cases when property changes leading to degradation can be detected at early stages (typically by means of high-

sensitive surface analysis instruments), an exposure set-up employing in-use conditions, i.e. similar designs as for long-term exposures, can be utilised. 2.2.3 Examples of some test procedures for thermal systems The (former) Swedish national testing and research institute (SP) has developed a certification system for e.g. solar collectors and heat pumps etc. named P-märkt. The solar collector certification procedure contains of two testing steps. Step one consists of various laboratory tests (material and thermal performance) where the collector is exposed to different loads. In step two, the collector is tested (material performance) by outdoor exposure at stagnating conditions. If the collector passes these tests and an agreement for routines of future quality control has been agreed upon between SP and the manufacturer, the collector is declared P-märkt (SP, 2005, a). The heat pump certification procedure (SP, 2005, b) is based on ensuring that the following requirements are met by the product: performance, safety and construction, documentation and quality assurance of manufacturing. Neither the solar collector nor the heat pump certification procedure includes long-term performance testing and evaluation. An extensive research on solar collector material durability has been made in the IEA Task X of the International Energy Agency Solar Heating and Cooling programme (Carlsson et al., 1994). The work was organised as a case study in which commercially available selective absorber coatings were studied. These coatings are used in glazed flat plate solar collectors for attaining Domestic Hot Water (DHW). An accelerated test procedure was developed to test the lifetime performance of the absorber coatings (ISO/CD 12592.2). Paper I (Stojanović, 2005) appended in this thesis gives a more detailed account. 2.3 METHODS AND APPROACHES FOR SERVICE LIFE PREDICTION

MODELLING In order to make computable SL predictions and assessments, the attained information (listed below) from test procedures and previous experiences has to be utilised in a mathematical modelling procedure (see also Eq. 1). degradation agents degradation mechanisms degradation environment characteristics magnitude of material or component degradation response material or component performance change due to degradation performance requirement

There are a number of fundamental approaches when perceiving and performing SL prediction modelling, some of which will be presented and discussed in this section. 2.3.1 Physicochemical and empirical modelling As pointed out in the beginning of chapter 2, the factors affecting the performance-over-time, hence the SL itself, are generally agreed upon as being stochastic. Besides the factor inherent variability, the sheer number of involved factors and their complex degradative actions and

interactions, prevents performance-over-time and SL functions from being derived by analytical or numerical modelling; of some stringent mathematically described physicochemical course of events (causality of some law of nature), see also (Marteinsson, 2005). This brings the necessity of aid by empirical or semi-empirical modelling, which takes into account the established dominant degradation agents of some physicochemical bound degradation mechanism. In general, an empirical modelling process involves five steps:

1. collecting data 2. analysis of data 3. model selection 4. parameter estimation 5. model validation

An empirical regression modelling approach is exemplified by the dose-response function, which is discussed more thoroughly in section 2.4. Physiochemical models are mathematical descriptions of a causality of some law of

nature. The model mathematically describes the causality, by having all the factors affecting the outcome as input values in the expression. The model is not case dependent and gives ‘correct’ predictions/calculations (of a course of event) by applying the inbound input values of each case, e.g. see also Marteinsson (2005). A physicochemical model can in it-self contain empirical notations that are based on tests and observations that describe some causality (see Fig. 5); however, without having profound knowledge of the physicochemistry in its essence. An example of this discussion are the mathematical expressions that model the phenomena of heat & mass transfer, e.g. see discussions by Holman (2002).

Fig. 5. A Venn diagram that schematically describes the derivation of a heat-transfer expression (regarding convection).

Thermo dynamics

Fluid mechanics

Empiricism

HEAT-TRANSFER

Empirical models are based on results from tests and surveys (general observations) by using statistical methods. These models tentatively quantify the influence of presumed dominating factors affecting an outcome. They will be case dependent, as they are based on data from specific post-studies. The models may be used for predicting/calculating other similar scenarios, by assuming that the process is in general consent with the course of events of the derived model. The model is a purely mathematical expression and does not give any physicochemical causality description. It can be said that the calculation is a ‘black box’ procedure.

A semi-empirical modelling approach is a procedure where a combination of

physicochemical and empirical regression models is used; in order to describe a course of events. An example is the modelling and calculation of concrete reinforcement corrosion, e.g. see Hallberg (2009) and Gehlen (2000). The physicochemical expression of diffusion (mass transfer), in combination with additional empirical modelling, is used to calculate/model the concrete carbonation or chloride ingress (1. the initiation phase). When a certain level of carbonation or chloride ingress is reached, the concrete reinforcement corrosion starts; whereby the corrosion is calculated/modelled with a dose-response function (2. the propagation phase), see Figure 6.

Fig. 6. A schematic figure of the course of events for concrete reinforcement corrosion. 2.3.2 Probabilistic and deterministic modelling In a sense, the common engineering way of preserving, expressing and modelling a semi- or empirical course of event, is thorough determinism. While this prevails, in reality the performance-over-time and SL of materials and components (in this case) have ‘as generally agreed upon’ stochastic outcomes (large scatter). This implies that derived models should pre-eminently be expressed as probabilistic (density) functions, as opposed to deterministic (see Fig. 7). An example of a deterministic approach is the derivation of dose-response functions (see section 2.4).

Concrete reinforcement corrosion

Initiation Propagation

Fig. 7. A schematic figure of deterministic (to the left) vs. probabilistic empirical modelling (to the right). The probabilistic way of perceiving performance-over-time and SL of e.g. materials and components is known as Reliability based Service Life Prediction (RSLP). When having the probabilistic distributions of a load and the resistance of e.g. a structure, the probability of failure or accepted failure can be calculated (see Fig. 8 and Eq. 2). A simple example of RSLP is presented in Figure 8, which shows the distribution of a load or requirement and resistance or performance. The area where the two distributions coincide (intersection area) in Figure 8, represents where the probability of failure occurs. In order to attain the failure probability limit, a target value for the maximal accepted failure probability is set (Eq. 2). Note; Eq. 2-4 that are presented in the following text are hypothetical formulations. Fig. 8. A schematic figure presenting the steady-state RSLP concept. targetfailurefailure PPxLxRPP (2)

The example in Figure 8 and Eq. 2 presents a steady-state case where the mean-value and shape of the distributions are constant over time. In reality, these functions will vary over time (time dependent), hence adding an addition dimension to the RSLP procedure (see Fig. 9).

Time Time

Density

Load / requirement

Probability of failure

Resistance / performance

Value (x)

Figure 9 and Eq. 3 schematically present the full dynamics of RSLP, where the distributions of resistance/performance and load/requirement are time dependent. Fig. 9. A schematic figure presenting the time dependent RSLP concept (similar to Fig. 1) (Jernberg et al., 2004).

targetfailurefailure PtPtxLtxRPtP ,, (3)

As the resistance/performance and load/requirement functions coincide, the probability of failure increases. The time dependent probability function representing this course of events, is presented in Figure 9 as the SL distribution (see also Eq. 1); the hypothetical SL probability density function is presented in Eq. 4. As previously discussed and presented in Eq. 2 and 3, in order to stay within the SL failure probability limit, a target value for the maximal accepted failure probability is set (see Fig. 9 and Eq. 4). targetSLfailureSLfailure PtPtSLPtPtxLtxRftSL ,, (4)

Further discussions and examples on RSLP, are presented by e.g. Sarja and Vesikari (1996) and Jernberg et al. (2004). In reality, RSLP of construction works face some difficulties concerning durability assessments. The primary obstacle is the lack of empirical data (making it difficult to perform probabilistic distribution modelling) and general performance-over-time functions of material and component degradation. This is in direct consistency with the fact that material and component degradation is a mainly slow course of events with vast time spans, making the task of attaining data demanding and time consuming. The reliability design method is today widely and successfully used in structural design, where probabilistic calculations are made on loads and strengths.

Resistance / performance- function

Load / requirement- function

Distributions

Time (t) Mean-lifetime

SL distribution

Accepted failure probability within a time span

Density

2.3.3 Mathematical methods of statistical modelling There are a variety of different approaches for mathematical methods of statistical modelling of empirical data. To mention a few, there are a number of different distribution models e.g.: Gaussian, Weibull, Gamma, Beta etc., which can be used for probabilistic distribution modelling, depending on the scatter of data (Jernberg et al., 2004; Martin et al., 1996). Besides different distribution models, a variety of functions may be fitted (regressed) to a dataset by means of regression modelling, thereby attaining a function that approximates empirical data representing a course of events. While there are a wide variety of approaches for mathematical methods of statistical modelling, two specific approaches/methods will be presented in more detail in this section: the Weibull distribution the Markov Chain model

These approaches are and have been widely used in SL prediction modelling of construction works. The Weibull distribution The Weibull distribution has emerged as being the most widely used and applied distribution for durability/SL or material strength modelling of technical systems, since it is flexible enough to model a variety of data sets. The variable parameter x, in the distribution (see Eq. 5 and 6), can be seen as time or a load. Statistical data from an empirical study on failure (of e.g. a number of technical units in service) makes up the bulk of information on which the distribution modelling is performed. Density function (Murthy et al., 2004):

x exp)(1

for x (5)

Cumulative density function (Murthy et al., 2004):

x exp1)( for x (6)

The following parameters are:

0 The scale parameter. It stretches out the distribution 0 The shape parameter. It allows a distribution to take on a variety of

shapes, depending on the value of the parameter. 0 The location parameter. Its effect is to translate the graph, relative to the original distribution ( = some origin value), a number of units left or right on the horizontal axis.

A number of type cases (to keep in mind) of the Weibull density function are when the shape parameter has the values as presented below. β ≈ 3 – 3.5: the density function is approximately symmetrical and reminds of the normal distribution β < 3: the density function is skewed to the left β > 3.5: the density function is skewed to the right Figures 10 and 11 show a number of graphs, which represent the Weibull distribution as a density and cumulative density function. The parameters are set to = 40, = (as presented in the figures; denoted as B) and = 0 in the figures.

0 20 40 60 80 100 120 140 160 180 200

Time (years)

B=1.5 B=3 B=5

Fig. 10. The Weibull distribution (density distribution) at = 40, different and = 0.

0 10 20 30 40 50 60 70 80 90 100

Time (years)

B=1.5 B=3 B=5

Fig. 11. The Weibull distribution (cumulative distribution) at = 40, different and = 0.

In order to attain a distribution which fits the data scatter from e.g. an empirical study, the parameters in the distribution have to be estimated. The procedures for estimating model parameters can be broadly classified into two major groups (Murthy et al., 2004): Graphical methods

In graphical methods, the estimates are obtained from plotting the data. The probability plotting involves a physical plot of the data on specially constructed probability plotting paper, whereby the parameters of the Weibull distribution can be estimated.

Statistical methods

They are more general and applicable to all kinds of models and data types. An example of a statistical method is the Maximum Likelihood Estimation (MLE) approach.

Examples on the application and use of Weibull distributions for probabilistic SL modelling are presented by e.g. Martin et al. (1996), Jernberg et al. (2004) and Martiensson (2005). The Markov Chain model The Markov chain model is a series of states of a system that has the Markov property. In time the system may have changed from the state it was in the moment before, or it may have stayed in the same state. The change of states is called transitions. A series with the Markov property is a sequence of states for which the conditional probability distribution of a state in the future can be deduced using only the current state; no additional information is given by the post-states to the process. In other words, the past states carry no information about future states. A process with the Markov property is usually called a Markov process. Consider a stochastic time process, which has a discrete sequence of random variables

described as NnnX , within a finite discrete state space S , where n represents the time

steps within a time period of N . The Markov property is mathematically expressed as: nnnn iXiXP |11 SiiiNn nn 01 ,...,, (7)

Whenever the state happens to be ni , there is a probability P that the next state is equal to

The example presented in this section, assumes that the Markov process is homogenous (stationary in time), as the transition probability functions depends only on the considered time interval n . Furthermore, the probability that a (some) current state is moving from one to another (or being stationary), is given by the transition probability matrix matrixP (of the probabilities ijP )

as presented in Eq. 8.

matrix

The transition probability function follows that 11

jijP .

The state vector for the Markov process is calculated as presented in Eq. 9, when the initial

probability state vector nXP and transition matrix matrixP are known.

matrixXX PPPnn

The main factors that have to be determined for making a Markov chain calculation, is the

initial state vector nXP and the transition matrix matrixP .

The Markov chain method is a procedure which is useful for performing SL predictions, based on data from e.g. a survey of some material or component degradation. Data on ratings based on a predefined condition rating scale (ordinal, of some degradation) is processed and presented as the probability that a condition class is moving into the next, at a certain time interval, (Eq. 8). Examples on the application and use of the Markov chain modelling procedure for SL prediction are presented by e.g. Sarja and Vesikari (1996), Hallberg (2006) and Hallberg (2009). For a more thorough mathematical exemplification of the Markov chain method, see e.g. Isaacson and Madsen (1976). 2.4 DOSE-RESPONSE AND DAMAGE FUNCTIONS The environmental effects on material, component and system degradation are an important aspect of SL prediction. A degradation model or dose-response function is most often empirical and deterministic. It is based on measuring the effects of degradation agents acting on a specific material or component. The various functions are based on regression techniques and tend to describe the environment where the measurements (on which they were based on) were made. It is therefore important to choose a model that correctly regress the degradation agents and mechanisms considered important for the component situated in the environment in question. A schematic flow chart of a dose-response material degradation modelling procedure is presented in Figure 12.

Fig. 12. A schematic flow chart of a dose-response material degradation modelling procedure. Inspired by Haagenrud (1997). As an example of a dose-response function, the corrosion of carbon steel (Eq. 10) can be taken (Kucera et al., 1986). It aims to empirically model the physicochemical connection between the material degradation and the degradation factors or agents of its exposure environment. The model is based on an 8-year exposure period at 32 test sites in rural, urban and marine environments in Scandinavia.

59.02 1442.077.0 tClSOM Fe (10)

MFe: Reduction of material thickness (m) SO2: Outdoor concentration (g/m3, mean-value per year) Cl: Outdoor concentration (g/m3, mean-value per year) t: Time (year) The dose-response function as such does not give any information about the SL. By applying performance requirements or limited states for allowable degradation of the material or component, will transform the dose-response function into a damage function (see Fig. 13) that provides information of the performance-over-time and SL. An example is shown in Figure 13, which is based on the dose-repose function presented in Eq. 10 (carbon steel corrosion). The function is applied with exposure environment input data for Gävle, Sweden in 2003 and a fictive limit state. It is assumed that the carbon steel corrosion proceeds at the same rate as described by the dose-response function for the correlated 8-year period. There are a number of available dose-response or damage functions for various materials, e.g. metals, natural stones and coatings, in different locations/regions, see Henriksen (2004); but far from every material, combination of materials, locations/regions and type of degradations have existing functions. The example above also points out that the availability of data/knowledge can be insufficient. Much work is being done on defining dose-response functions and research is ongoing throughout the world, e.g. ICP-Materials (2009).

Deterministic empirical regression modelling of a physicochemical degradation mechanism

Exposure environment

Dose-response function

Degradation

material response

0 5 10 15 20 25 30 35

Time (years)

Dose-response function (corrosion of carbon steel)

Limit state

Time to failure

Fig. 13. An example of the transformation from a dose-response function (Eq. 10, Kucera et al., 1986) into a damage function based on the corrosion of carbon steel. The utilisation of dose-response functions is a concrete approach for assessing and calculating the durability and SL of materials, although it must be recognised that the method itself is more or less a rough approximation. As previously mentioned, it is generally agreed upon that the variables affecting the durability (hence the SL itself) are stochastic due to the lack of knowledge and complex causality of exposure environment, agents and material degradation. This implies that empirical modelling must be used for deriving these types of dose-response functions, as a solely physicochemical model is not achievable. The empirical data, which dose-response functions are based on, are taken from test specimens (of e.g. a particular material) that have been exposed to an exposure environment at different locations during a period of time. The degradation quantification (e.g. the oxidation in the case of metals) is the mass loss or increase of the exposed material specimen, caused by degradation agents at the field exposure location/locations. A dose-response function is then set-up for this type of material and a number of dominating degradation agents at these particular locations, by means of regression modelling (see Fig. 12). The calculated results (with the derived function) are deterministic and the performed SL assessments are seen as quantitative. Dose-response functions and the methodology that they are based on, leave a room open for discussing the adequacy and feasibility of the approach. The fact that the function is based on regression modelling makes it only applicable in the environment (or similar environments) where the objects are studied, as regression modelling in purely mathematical and does not describe the physicochemical process in its essence. By concentrating the studied objects or spot checks to a particular region/location and its environment, the accuracy of derived functions, given that the dominating degradation agents are identified and included in the model, will increase. When the dose-response function is established, the degradation parameters (agents), coefficients, exponentials and constants are fixed, making the function unreceptive to changes in the outdoor regional environment. As an example of this scenario, some agent diminishes as others increase which changes the rate of degradation. Other barriers that arise are the reliability of dose-response functions applied to structures, in comparison with material specimens. The complexity of a structure can result in different climatic and environmental conditions on a single structure, which greatly affects degradation rates. Dose-response functions are more or less established under controlled experimental

conditions, e.g. see Henriksen (2004), and a major task is the transition to real structures, as pointed out by Haagenrud (1997). Further discussions about the reliability of the methodology and dose-response functions as such, are the existence of synergetic effects between agents, wet-dry cycles, and possible presence of agent threshold values and identification of dominating agents. As discussed by Haagenrud (1997), the question is whether characterising degradation agents as mean-values (as often done for a particular location or region) and acting independently (as assumed in most cases) is adequate, and if it is possible to isolate the predominant degradation agents from agents that have secondary effects. Several laboratory experiments have shown that agents act synergistically and that dose levels that are under a certain threshold only contribute to a negligible rate of degradation, (Carlsson et al., 1994) and (Martin et al., 1996). 2.5 PERFORMANCE-OVER-TIME As discussed in chapter 2, the performance-over-time for any construction works is in general a function that describes a specific measurable performance characteristic, in a certain service/exposure (degradation) environment and during a time period. As the change in performance (in this context) is an implication of degradation in time, the transformation of a degradation process/function into performance change, constitutes the fundamental procedure in order to obtain a performance-over-time function. The definition of performance is vital as it can be related to different functionalities on different levels e.g. such as: material, component or system; regarding degradation, it always occurs on the material level (see Fig. 14). Note; when a component solely or predominately consist of a single material, the degradation and performance of the material and component ‘unifies’ (are the same). An example is the degradation of e.g. a steel (material) beam (component) due to corrosion. In this case it is more appropriate to use the classification component degradation, hence performance. Depending on the performance definition, the effect of material degradation on performance can involve a variety of transformations, as the time dependent relation between the degradation and performance-over-time may consist of various disproportionalities (see Fig. 14 and 15). Furthermore, the transformation may be performed in several steps, in order to bridge different performance levels (see Fig. 14). This procedure may facilitate the overall degradation to performance transformation. A factor that can additionally complicate the transformation (especially regarding system performance) is the occurrence of chain reactions. As a specific material degrades, its individual performance reduction may not only singularly affect the system performance, but also the durability of other materials/components in the assembled system; hence multiple material/component degradations are synergistically affecting the system performance. This transformation complexity presents a major obstacle for attaining (as in this example) a system performance-over-time function based on material degradation.

Fig. 14. A chart that schematically presents the interaction and transformation of degradation and performance at various steps and levels, hence enabling SL prediction. Due to transformational complexities or lack of knowledge on material degradation, information on damage and SL may be obtained from statistical surveys.

Fig. 15. An exemplification of a hypothetical disproportionality between degradation and performance-over-time, where performance-over-time is a function of the degradation function.

COMPONENT PERFORMANCE / SL

MATERIAL DEGRADATION

MATERIAL PERFORMANCE

SYSTEM PERFORMANCE / SL

TRANSFORMATION

Performance-over-time function

Degradation function

Time (t)

B[A(t)]

The obtainment of a performance-over-time function enables not only to assess when in time a certain performance level is reach, but also at what rate performance changes. The combination of this information supports the decision-taking of setting a performance requirement, hence enabling SL prediction. The transformation of material degradation into material, component or system performance can be performed (if possible) by theoretical calculations or computer simulations. A hypothetical example can be an arbitrary structure that has a share of steel beams. Let’s say that the steel starts to corrode due to the exposure environment, thereby degrading the beam material, hence the beam (component) performance (strength) due to the weakening effect of corrosion. The effect of steel corrosion on beam strength can then be transformed in to structural integrity (system performance) by theoretical calculations or computer simulations. When the establishment of a performance-over-time function (based on material degradation) is not viable, due to transformational complexities or lack of knowledge on material degradation, information on damage and SL (given that a performance requirement is defined and set) may be obtained from statistical surveys (see Fig. 14). This approach does generally (depending on the scope of the survey) not render a performance-over-time function as it attempts to statistically estimate a lifetime period; nor is the damage and SL correlated to the service/exposure (degradation) environment, it represents the conditions from where the survey was performed. 2.6 THE ARRHENIUS EQUATION If the temperature of some chemical reaction is altered, so does the speed with which the reaction proceeds. This course of events is mathematically expressed with the Arrhenius equation, Eq. 11 (Atkins and Beran, 1992).

lnln (11)

A: the pre-exponential factor (unit) ET: the activation energy (kJ/mol); the amount of (provided) energy required to start a chemical reaction/process k: the rate constant (unit) R: the ideal gas constant (kJ/K·mol) T: the absolute temperature (K) The parameters ET and R are constants and ET depends on the chemical reaction. The fact the heat accelerates a chemical reaction, hence thermally bound material degradation, makes the Arrhenius equation appropriate for modelling thermally induced accelerated short-term degradation testing. The basic concept is to set-up a laboratory test where a thermally bound degradation mechanism, acting on a material or component, is accelerated in a climate chamber. An important task is to make sure that the change in temperature is the solely factor governing the rate of degradation. By exposing the material or component at different temperatures, the activation energy TE parameter is determined by ways of regression analysis of experimental data. The data generally contains: a quantitative degradation measure, exposure temperature and elapsed time. In order to make the accelerated test useful

for predicting in-service degradation, the degradation processes taking place under accelerated aging tests conditions, must be preceded by the same dominating agents and mechanisms as those during in-service conditions. As an example of the use of the Arrhenius equation for thermally induced accelerated short-term degradation testing, is the Task X study (Carlsson et al., 1994). Results from different accelerated tests performed in the study, were used to mathematically model the lifetime performance of selective absorber coatings used in glazed flat plate solar collectors, see also Paper I (Stojanović, 2005) appended in the thesis. When applying the mathematical model, time transformation functions in terms of the Arrhenius equation was used. The results from the accelerated high-temperature degradation tests in the Task X study were modelled by applying the Arrhenius equation for the temperature dependence expressed as:

nSnRT cTTREy

11 lnln (12)

Values for ET and the parameters c0-cN are determined by way of regression analysis from experimental data. To transform the data from the high temperature accelerated tests into time under in-service conditions, the effective mean-temperature, TeffT , , is introduced and

expressed as:

Teff dT

ET (13)

)(Tf is the annual-based frequency function for the absorber in-service temperature. The

effective mean-temperature is defined as the constant temperature resulting in the same degradation in the same time period as the fluctuating load. TeffT , is then applied to the

Arrhenius equation for a time transformation into in-service degradation:

RS eyy (14)

Associated studies on Arrhenius equation modelling of accelerated degradation of solar collector materials, are presented by e.g.: (Brunold et al., 2000), (Carlsson et al., 2000, a), (Carlsson et al., 2000, b), (Carlsson et al., 2004, b) and (Köhl et al., 2005). 2.7 THE FACTOR METHOD In a specific design or maintenance case, the SL of some component (as an example) is seldom known. In order to gain this knowledge, it is required to use available information on a reference component situated in a reference in-use condition and which has a reference SL. This information will be modified to be applicable to the intended design, the actual in-use conditions or maintenance situation. The Factor Method is a procedure that has been developed with the intention to systematise these types of SL assessments. The method is

standardised and described in the standards ISO 15686-1 (ISO 2000) and ISO 15686-8 (ISO 2008), and by e.g. Hovde (2000), Jernberg et al. (2004), Marteinsson (2005) and Hovde (2005) to mention a few. The method is not a degradation model as it only means to estimate the SL and not the performance-over-time. The method is formulated according to ISO 15686-1 (ISO, 2000) as follows: GFEDCBARSLCESLC (15) ESLC: Estimated SL of a component or assembly RSLC: Reference SL of a component or assembly A: Quality of component B: Design level C: Work execution level D: Indoor environment E: Outdoor environment F: In-use conditions G: Maintenance level A window with a wooden frame can be taken as a simplified example of the Factor Method’s use and function, as presented in the standard ISO 15686-1 (ISO, 2000) and by Jernberg et al. (2004). The window has a well-defined RSLC of 20 years. Let’s say that this particular type of window will be installed in a building, which has similar conditions as the RSLC, except for factor E. The outdoor environment at this particular site is harsher then where the RSLC was established. It is conclude that the outdoor environment will have a modifying factor of 0.8, hence the 16118.0111120 ESLC years. Discussions and examples on how to attain knowledge and set modifying factor values, is presented by Marteinsson (2005). As previously discussed, the Factor Method is a procedure that has been developed with the intention to systematise SL assessments of construction works when test data is lacking or does not fully match the anticipated conditions of use, in order to attain a tool which can be used at the design stage. The method is based on a RSLC and a number of modifying factors, which transforms the RSLC to an ESLC of the studied object. The considered modifying factors are both of qualitative and quantitative character and some factors can be allocated to the following groups as presented by Marteinsson (2005). Qualitative: Some of the agents such as the effect of design (B), workmanship (C)

and maintenance (G) are difficult to give a value to except on an ordinal scale.

Quantitative: The environment (D, E) can be valued or compared on an interval scale given that enough information is available in form of characterisation of degradation environments or degradation functions. The comparison can be made as a ratio between design or maintenance cases and a reference case.

Factors A and F are not as easily defined since they posses the characteristics of both groups. Factor A is dependent on material properties, design and workmanship of a product or component, while factor F represents a wide range of actions and usage, some of which are quantitative whilst others are qualitative. The fact that a majority of the modifying factors are qualitative (among other things) raises hesitations of the method’s reliability and feasibility, in order to assess and estimate the SL. One major objection against qualitative involvements is the lack of objectivity. This is the case when it comes to a person or a group of people (designers, engineers etc.) that have to decide to what extent a factor should modify the RSLC, based on their own experiences and concepts, as useful quantitative data is lacking. The decision will clearly be subjective or inter-subjective. However, the Factor Method should not be entirely dismissed due to the involvements of qualitative data and methods. The question is if a relevant factor, which is based on a value derived by a qualitative method, can objectively be replaced by a quantitative notion and is there any point in doing so. A further objection against the Factor Method (or any other deterministic SL prediction method) is that the method is deterministic instead of probabilistic. If a probabilistic approach is used, the precision in each factor and outcome of the method could be evaluated, e.g. given as a confidence interval. As discussed by Marteinsson (2005):

“By using probabilistic functions instead of deterministic values, for the factors, will not change the uncertainty in results, as the functions themselves will not be known with any certainty (lack of data, see discussion in section 2.3.2)”

As the discussion shows, the Factor Method exhibits obstacles for enabling it to assess and forecast the SL with precision. The available dose-response functions can be seen as ‘corner stones’, as they provide the method with the possibility for comparison, in terms of ratios between design cases and a reference case. But as the previous discussion points out, dose-response functions themselves display flaws. A study on the application of the Factor Method for SL estimation of district heating distribution networks, regarding pipe leakage, is presented in chapter 9 and Paper VIII appended in this thesis. 2.8 LIFE CYCLE MANAGEMENT SYSTEM Until 2003, the Building Materials Technology group at the Centre for Built Environment - University of Gävle have completed three consecutive EU-projects (Haagenrud et al., 1999; Haagenrud, 2001; Sarja, 2004). These projects, promoted by an increased European focus on R&D on sustainable construction, have in several steps developed methods, systems and tools for predictive maintenance management in order to meet the demand on sustainability during the whole SL of construction works. A result of the projects is a predictive and generic Life cycle Management System (LMS), which aims at supporting all types of decision making and planning of optimal design, Maintenance, Repair and Refurbishment (MR&R) activities of any construction works and systems therein. Due to its predictability function, it is possible to adopt short-term as well as long-term planning in which decisions may be based on

economical, environmental, safety, cultural and social values etc. According to the project (Lifecon) the novelties of the LMS are (Sarja, 2004): Predictive characteristics: The LMS includes integrated performance analysis

functions that are capable of predicting the functional and performance quality of a structure and its components depending on the conditions of its environment.

Integration: Aspects of sustainable development such as human requirements, life

cycle economy, life cycle ecology and cultural requirements are included in MR&R planning, design and execution process.

Openness: Freedom to apply the LMS into specific applications using selected

modules and freedom to select methods developed within or outside the LMS system. The LMS is a system by which the complete system (or parts thereof) works in co-operation or as a complement to existing business support systems, see e.g. Sarja (2006). The system is module-based, where each module represents a sub-process within the maintenance management process. Figure 16 shows the structure of LMS (6 modules) and its connection to other business support systems. The first module, i.e. the Inventory Registration Module, contains systematic registration, classification and description of technical and administrative data of the objects/systems. The Condition Survey Module includes systematic recording of condition data. This includes guidelines and protocols for condition assessment and survey in order to obtain consistent and reliable inspection/observation results on the items and their environment. The ‘heart’ of the system is the Service Life Prediction Analysis (SLPA) module. This module contains applicable degradation models, which describe the loss of performance over time of a material, component or system. The Maintenance Analysis Module includes systematic analysis of different MR&R alternatives by utilising the predictive functions of the SLPA module in order to evaluate the efficiency of the MR&R alternatives. The Maintenance Optimisation Module contains models for optimisation of those MR&R actions suggested in the Maintenance Analysis Module. It takes into account a number of aspects such as Life Cycle Cost (LCC) and Life Cycle Ecology (LCE). The final module within the LMS is the Maintenance-Planning Module, which serves to establish optimised long-term plans of MR&R actions. Aside from the long-term planning aspects offered by LMS, it serves as an archive for the client. The Condition Survey Module is in essence a collection of inspection/observation data and experiences. Together with a Damage Atlas used for systematic surveillance and a collection of applicable norms/standards in a help menu of LMS, experience and routines of the client organisation will be maintained independently of the volatility of personnel, i.e. retirement, illness. Implementation of the LMS into an organisation and its activities requires adaptation and development of the LMS system itself. This means that the complete and/or parts of LMS has to be adapted towards a presumptive user in order to suite user needs and requirements; adaptation of methodology, structure, models and design of each module in question. Extensive R&D on LMS has been made by Hallberg (2009).

Fig. 16. Structure of the module based LMS. 2.9 REMARKS As a first impression, the durability and SL assessment of construction works does not present any obstacles. There are various degradation functions, assessment approaches and tools, as well as a provided standardised ISO method. But after some reconsideration, it becomes obvious that these assessments are not as straightforward as they first appear. On the contrary, degradation is a complex process and the knowledge of it and its effects on construction works, in terms of e.g. structural, economical and environmental performance is not always entirely known. Due to the lack of knowledge and information, the R&D in this field is focusing on attaining knowledge and developing tools/models that are based on the combination of physicochemical models (to as large extent as possible) with empirical data, which can be both quantitative and qualitative, and then modelled as deterministic or probabilistic functions of some sort. Questions that are vital to this discussion are if the derived models/tools are adequate despite the lack of knowledge and high level of complexity. As discussed by Marteinsson (2005), building components can be classified into three groups: High-risk objects: crucial for the safety of a structure, expected to outlive the

structure with minimal maintenance, difficult or expensive to replace. Medium-risk objects: considerable economic loss or great inconvenience.

Service life analysis

1 2 3 4 5 6 7 8 9 1 1 1 1

Action 1 Action 2 Action 3 L=3.2 2 + 5

1. Pipe 2. Pump 3. HE ……. …...

Inventory registration

Maintenance analysis

Maintenance cost Träfönster

Åtgärd Tidsåtgång Timpris Arbets- kostnad Material-

kostnad Total- kostnad inkl. moms

2 glas 1luft <1m2Byte komplett 2, 31 74 200 274 3430,0Ommålnin 1 33 33 7 40 506,2

2 glas 1luft >1m2Byte komplett 4, 31 130 320 450 5627,5Ommålnin 1, 33 46 127, 589, 736,8

2 glas 2 luftByte komplett 4, 31 139 320 459 5743,7Ommålnin 2 33 66 18 84 1050,0

Maintenance planning

jghj jghj jghj jghj jghj

TIDPLAN jghj jghj jghj jghj jghj

TIME PLAN

TIDPLAN

TIME PLAN

TIDPLAN jghj jghj jghj jghj jghj

TIME PLAN Service life

1 2 3 4 5 6 7 8 9 1 1 1 1

Actio Actio Actio

Service life

1 2 3 4 5 6 7 8 9 1 1 1 1

Actio Actio Actio

Maintenance optimisation

InspectionProtocol

…………..………….………….

Condition survey

Work Order city block ………….. …………. ………….

Service life prediction analysis

Life Cycle Management System

Business Support System

Low-risk objects: easily replace at a moderate cost, fault criteria are poorly defined, degradation leading to faults is easily seen and replacement can be planned in advance.

SL information is used in different ways. Demands for reliability and precision of the figures will vary between fields of applications. There are rigorous demands on reliability for components that form a part of the structural system in codes and standards, as an example; technical faults can occur suddenly and might result in safety risks. When it comes to materials and components that are classified as medium or low-risk objects, the SL assessment reliability is not required to uphold the same level of accuracy. These figures can be used in comparison of different products in SL planning and various economical and environmental analyses, during the design phase. The ability to assess or predict the durability and SL of materials, components or systems is important for the structural, economical and environmental aspect of construction works. But the available methodologies, tools and models (as discuses in this thesis) lack the precision for making accurate predictions and assessments due to vast complexities in the interaction between the exposure environment, agents and material degradation. This raises the question of what level of accuracy is needed, and whether is it necessary to have high accuracy. The answer is yes, if the intentions are to model the durability and SL in its essence and use it as a governing designing and optimisation tool in high-risk and (to some extend) medium-risk object projects. However, many components which can be seen as belonging o the medium or low-risk group, can use current knowledge and methodologies in e.g. design work for comparison of different products, in-service scenarios and planning of maintenance. The current available methodologies and knowledge, which is (and has the intention to be) used, is a tentative approach for assessing and predicting the SL and durability of construction works. According to ISO 15686-1 standard (ISO, 2000), the objective of forecasting the SL of a building, component or system, is to establish whether or not the SL can be expected to exceed the required design life with adequate reliability. The forecasting of SL should: reduce uncertainty seek to use available data of known quality take account of variability be used to guide rather than dictate

It is difficult to say whether one SL prediction method is better than another, as all-current available methodologies are more or less imprecise, making it unsatisfying to compare their accuracy. However, it is generally agreed upon that the most reliable and valid approaches are semi-empirical or dose-response (damage) functions. But as previously pointed out in this thesis, not all materials/components, locations/regions and types of degradations have available semi-empirical or dose-response functions, making it necessary to use other ways of forecasting, e.g. via the Factor Method or by Markov chain modelling. A major barrier for further progress concerning the durability and SL aspects is the lack of knowledge and implementation of the damage function approach (Haagenrud, 1997). Further R&D is needed for improving and attaining better durability and SL prediction methodologies and tools in order to attain sustainability in construction works. The possibilities of computer-

based modelling and simulations of e.g. Heat and Mass Transfer mechanisms (radiation, conduction, convection and diffusion), Computational Fluid Dynamics (CFD), Structural mechanics and component-systems etc. have increased considerably through advancements in simulation methodologies and techniques. This gives the possibility for detailed simulations and analysis of construction works, enabling improvements of the current methodologies.

3 GENERAL DESCRIPTION ON SOLAR ENERGY, HEAT PUMPS AND SOLAR-ASSISTED HEAT PUMPS

The use of solar collectors for heating purposes has grown in Sweden during the last decades. The amount of sold collector area has steadily increased from 5000 m2 in the beginning of the 1980s to an amount of 20000 m2 in 2001. The now fastest growing collector applications are Domestic Hot Water (DHW) systems. These are installed to cover a part of the total hot water energy requirement. The target group for these systems is mainly single-family houses that rely on electrical heating and are in need of changing the DHW heater (Bengtsson, 2003). Installation and use of Heat Pumps (HPs) has also grown rapidly in Sweden during the last decades. Today, Sweden is one of the largest HP markets in Europe (Kjellsson, 2004; Eriksson, 2004). A majority of these HPs are ground-coupled where the heat exchanger is a borehole of 90 - 220 m depth (STEM, 2006), but also air-to-air and exhaust air HP systems are popular installations. During the 1980s, HP technologies were regarded as an ‘alternative energy technology’ which reduced the energy consumption and therefore the environmental impact. According to some up-to-date investigations, a residential electrically powered HP with a Seasonal Performance Factor (SPF) (Tepe et al., 2005; Kjellsson, 2004) of 2.5 - 3.0 will give an approximately equal CO2 contribution to the atmosphere as a heating system based on burning fossil fuel (STEM, 2002). According to the new Swedish building regulations (Boverket, 2008), HP installations that have an electrical power consumption that exceeds 10 W/m2 (per heated floor area at peak load) should be regarded as electrical heating, which means that the heating (energy) requirement is stricter in comparison to non electrical heating. It is therefore important to increase the SPF to meet these requirements and keep the environmental argument for installing residential HP systems. During recent years, there has been an increased interest in heating systems that combine HPs with solar collectors (glazed and unglazed), aiming to provide a higher energy and greater economical performance than individual solar collector or HP systems (Kjellsson, 2004; Ozgener and Hepbasli, 2007; Hepbasli and Yildiz, 2008). The combination of wood pellet burners (heaters) with solar collectors has also gained interest, e.g. see Persson (2006). Projects combining solar thermal energy with district heating have also been conducted, e.g. see Solar Buildings in Gårdsten (2009). 3.1 GLAZED AND UNGLAZED FLAT PLATE SOLAR COLLECTORS The general working principle of a solar collector is the absorption of solar radiation (primarily the wavelengths () 0.3–2.5 m, solar thermal range), which thereby is transformed into thermal energy. The absorber-plate is the main radiation absorbing component in the collector (see Fig. 17). The plate transfers the absorbed heat to the collector heat transfer fluid, which flows thought the component, hence increasing the fluid temperature. A glazed (flat plate) solar collector (as noted by the name) has the absorber-plate covered by a sheet of glass or equivalent cover.

The primary purpose of the glazing is to minimise heat losses from the absorber-plate, as the surface temperature increases beyond the ambient. Basically, the glazing can be described as having a ‘greenhouse’ function, with the following general descriptions: To transmit (short wave 0.3–2.5 m) solar radiation to the absorber-plate and block

(long wave 2.5 – ~50 m) infrared (IR) radiation emitting from the absorber. Absorbers and glazing can also be treated with wavelength-selective layers/surfaces, thereby blocking emitted IR radiation from the absorber-plate and the glazing itself, hence reducing heat losses and improving the collector performance.

To reduce convective heat loss. The protective glazing will create an air cavity (micro

climate), which will reduce the convective heat loss from the absorber-plate to the ambient (macro climate). An increase in the convection at the external surface of the solar collector will generate an increase in the total heat loss.

The energy performance of a flat plate solar collector (glazed or unglazed) can be calculated with the well-known the steady state energy balance model as presented in Eq. 16 (the Hottel-Whiller-Bliss model), (Duffie and Beckman, 2006). aifLRc TTUSFAQ (16)

A future development of the model presented in Eq. 16, is Eq. 17 (Fischer et al., 2004). The coefficients in the model are attained by specific collector testing and regression analysis, thereby correlating Eq. 17 with empirically attained collector performance data. The attained model (in Eq. 17) is semi-empirical and based on quasi-dynamic collector testing, which gives a mathematical expression of the (empirically adjusted) energy performance.

dTcTEcTTucTTc

TTcuGcGKFGKF

aLamam

amddenbben

)()(')()('

In general, Duffie and Beckman (2006) present a thorough description of different solar collector types, performances and modelling. An ingoing work on calculation methods of solar collectors is also given by Hellström (2005). E.g. Helgesson (2004) and Nilsson (2007) present work on Photovoltaic/Thermal (PV/T) solar collectors, with focus on solar concentrators.

(b) Fig. 17. A schematic drawing of a glazed (b) and unglazed (a) flat plate solar collector. A major difference between unglazed and glazed solar collectors is the absence of the glazing, which makes the Unglazed Solar Collector (USC) a simpler and cheaper construction. This results in lower working temperatures of the USC, as the absorber surface is directly exposed to the ambient (macroclimate), which will result in lower collector fluid temperatures. This is primarily due to larger convective and long-wave radiative losses from the absorber surface (see Fig. 17). Since unglazed collectors are working in an entirely different temperature range than glazed collectors, they are often operating together with other components in a system solution (e.g. solar-assisted heat pump system) which is needed in order to raise the temperature level and making it more useful for heating purposes, with the aim of giving an overall more efficient energy system. Yet, it is often desired to obtain as high temperature levels as possible. This can be achieved by means of various coatings on the collector, but also by assessing the useful energy gain by convection in a particular system solution. In general, if the heating is to be achieved by solar radiation, it is important to minimise convective heat losses as much as possible.

However, the scenario may also be to achieve heat absorption primarily by convection. At low out-door temperatures say some degrees above 0 C, without an influencing presence of solar radiation, the heat transfer fluid temperature may be raised a couple degrees. This temperature rise can be sufficient for heating a house with a HP. In this case, the desire is to have as effective convection as possible. A graph representing a comparison of solar collector efficiencies for glazed, unglazed and vacuum solar collectors is shown in Figure 18. The graph shows that solar collector efficiency (share of, by the solar collector fluid, net absorbed solar energy in relation to total incident solar energy) decreases as the temperature difference between the collector and ambient increases (the driving potential for thermal losses from the collector to the ambient).

Vacuum

Glazed

Unglazed

T solar collector - ambient

Fig. 18. An example of efficiencies for a number of solar collectors at various temperature differences between collector fluid absorbed heat and ambient when the incident solar radiation is 800 W/m2. Picture source: Kjellsson (2004). 3.2 THE HEAT PUMP SYSTEM The basic working principal of a HP (in heating mode) is that energy is transferred from a colder to a hotter body (reservoir) by supplying work to the process. Work in form of energy (electricity, mechanical movement, etc.) is essential for the HP process in order to be realised. In other words, the HP process will involve energy consumption to obtain energy transfer from the colder to the hotter reservoir. In order to evaluate how well this process performs, the term Coefficient of Performance (COP) is defined. It represents how much energy is transferred in relation to how much energy (work) is supplied to the process (see also section 5.2). For a detailed thermodynamic description of the HP process, see e.g. Moran and Shapiro (1993). A schematic drawing illustrating the technical concept of a HP or refrigerator system is presented in Figure 19.

Fig. 19. A schematic drawing illustrating the technical concept of a HP or refrigerator system. As Heat Pump Refrigerant: The circulating fluid in an evaporation-condensation process. Compressor: Compresses the evaporated refrigerant by sucking in vapour from the evaporator, thereby creating a low pressure and adding energy ‘work’ to the vapour, which attains a higher temperature (quality of energy/heat) and pressure; hence the high pressure side. Expansion valve: Regulates the mass flow and maintains the pressure difference between the evaporator and condenser. Low-pressure side: The present pressure in the part of the HP system where the refrigerant is evaporated, thus absorbs heat to the system.

Heat source: The source from which the HP system absorbs heat at low temperature via the brine and HP evaporator. Brine: A fluid that absorbs heat from the heat source and transfers heat to the HP evaporator (also called cold carrier). Evaporator: Where the refrigerant liquid (HP) absorbs heat from the brine, hence heat source, and with goes a face change, evaporates. High-pressure side: The present pressure in the part of the HP system where the refrigerant is condensed, thus emitting heat from the system. Heat absorber: A body or space that absorbs emitted heat from the HP process (condenser via the heat carrier), in order to obtain and maintain a higher temperature than the ambient. Heat carrier: A fluid that receives heat from the HP condenser and distributes the heat to other heat emitting systems, e.g. radiator circuit. Condenser: Where the refrigerant vapour (HP) emits heat to the heat carrier, hence heat absorber, and with goes a face change, condensates. 3.2.1 Commonly used heat sources The heat source used in a HP system is of great importance. The energy consumption by a HP reduces as the heat source temperature increases. Energy content of the heat source should be of a significant amount, so that only a minor or acceptable temperature drop occurs due to energy discharging. A decrease in heat source temperature, in time will directly decrease the efficiency (COP) of the HP. The temperature level on the heat emitting side of the HP is also of importance for the COP. A reduced temperature level on the heat emitting side will render a higher COP, hence the recommendation to have floor heating instead of a radiator circuit when installing a HP system for domestic heating. Normally, the maximum outgoing floor heating temperature is ~ +30 C, whilst for a radiator circuit it is +55 C (Warfvinge, 2001). Commonly used heat sources by HP systems in Scandinavia (Sweden) are: outdoor air exhaust air (ventilation) ground lake, river or sea (water) borehole (ground water)

The outdoor air is a convenient heat source. Its usefulness is unfortunately limited as the outdoor air temperature is low when the building heating demand is high (winter time). The problems arise when the outdoor temperature is at the same level as the lowest operating temperature in the evaporator, which is dependent on refrigerant type, HP design, component materials, etc. Another disadvantage when using outdoor air is freezing problems. At low evaporation and surface temperatures, the water vapour in the outdoor air may condensate and freeze, thus preventing heat absorption from the outdoor air.

Exhaust air in mechanical exhaust ventilation systems can also be used as a convenient heat source. It normally has a temperature of some +20 °C (in Sweden) and has an energy content which corresponds to ~20-30 % of the heating requirement of the building (single detached houses), if cooled to outdoor temperatures. The heat that is delivered from the HP commonly fulfils the heating requirement of DHW and the excess, if any available, is delivered to the space heating system. The ground can also be used as a heat source. In comparison to outdoor air, the ground has the advantage of lower temperature variations, hence a more stable heat source. In the southern parts of Sweden, the difference in temperature amplitude between outdoor air and ground at 1m depth is around 4 °C. In the northern parts it can vary up to some 15 °C. This means that during winter, the HP is working with a heat source that has a higher mean temperature than outdoor air; hence higher COP. Plastic pipes, that are buried at 1–1.5 m depth with a ~1 m horizontal spacing, are most frequently used as heat collectors. Normal heat output is 10–20 W/m pipe (Alvarez, 1990). Larger heat outputs than that is not recommended with regards to the lowering of ground temperature. A rule of thumb, during the above-mentioned conditions, is that the required ground area with collector pipes is five times larger than the heated floor area of a building representing a typical Swedish single family house. Lake, river or sea-water can also be used as heat sources. Heat can be collected from the water by two means: water can either be directly pumped to the HP or have a collector pipe placed in the water. Normal heat output is 15-20 W/m pipe for lake water collectors (Alvarez, 1990). Direct lake/river/sea-water systems cannot normally work in the winter season. The majority of the newly installed HPs in Sweden are ground-coupled, where the heat exchanger is a borehole (ground water) with a depth of 90-220 m (STEM, 2006) and a diameter of 0.114–0.164 m. A borehole is a convenient heat source in the way that it does not require any significant space (in comparison to ground collectors), and it maintains a ‘stable’ temperature. Average borehole temperatures in Sweden are around 10 °C in the south, around +7 °C in middle and about 3 °C in the north, at a depth of 100 m. A rule of thumb for a borehole situated in the middle part of Sweden is that ~20 m borehole per kW HP heating power is required (Kjellsson, 2004). The most normal design in Sweden is a single U-pipe, which is lowered into the borehole as an energy collector. Boreholes that are equipped with a single U-pipe are the cheapest solution but have the highest thermal resistance. A disadvantage that boreholes in Sweden today face is the installation cost. The main cost of a borehole installation is drilling. The price range is dependent on borehole depth, casing down to bedrock, bedrock and ground conditions. 3.2.2 The temperature dependence of heat pump COP The efficiency of a HP is often characterized by the COP, which indicates rate of heat flow delivered from the HP in relation to the rate of energy flow (electricity/work) supplied to the process. The relationship between COP and temperatures at which the refrigerant in the HP evaporates and condensate is expressed with the Carnot COP (Moran and Shapiro, 1993) as:

heat absorbedheat emitted

heat emittedCarnot TT

The Carnot COP presents the best possible theoretical performance of all processes (a refrigerant or HP process in this particular case) that work between two given temperature levels, one level at which heat ‘energy’ is absorbed into the process, one where heat is emitted, and with a sub-process where work is introduced/produced - independently if the process is a HP, refrigerator or combustion engine. It should be noted that the Carnot COP equation (Eq. 18) is derived with the assumption that the machine is working with four reversible processes, which constitute the Carnot cycle. A real machine ‘processes’ can only reach essential lower values of performance, as all real processes are irreversible. Despite that the Carnot-cycle is practically not achievable it still has a great engineering value. It presents the highest possible COP that a thermal machine, which is working between two temperatures, can achieve. Therefore, the design of a thermal machine should always strive to obtain performances that are as close to Carnot efficiency as possible. As the Carnot COP has a simple mathematical expression (see Eq. 18), consisting only of the heat absorbing and emitting temperatures, it can conveniently present the temperature dependence of HP COP. A simple approach for transforming (modelling) the Carnot COP into a ´real´ HP process COP, is by multiplying a modifying efficiency factor (see Eq. 19), which represents the efficiency of a real HP process in relation to the Carnot process (e.g. see Akander et al. (2008) or Paper V appended in this thesis). The value of the modifying efficiency factor can be obtained from HP unit testing. HP manufactures usually present test results on HP COP at different temperature levels, e.g. see IVT (2009). This data can be use in order to obtain a constant mean factor value, or a function based on regression, for a particular temperature interval. In other words, the modifying efficiency factor is a ‘finger print’ of a particular HP unit/model, which also is temperature dependent. Once a representative constant mean factor value or regression function is obtained, the Carnot COP can be transformed into a fair estimate of a ‘real’ HP process COP.

heat absorbedheat emitted

heat emittedestimate TT

In order to graphically exemplify the temperature dependence of HP COP, a normalised change in COPestimate (see Eq. 20) is presented in Figure 20. The normalisation is based on the temperatures T1.emitted heat = 40 C and T1.absorbed heat = 3.5 C. T1.emitted heat = 40 C represents an approximated mean outgoing radiator circuit (heat carrier) temperature, during the heating season, for an average Swedish single family house, geographically located in the Stockholm. In practice, 65 C is the maximum (refrigerant) temperature a HP can generate. Heat carrier temperatures are somewhat lower, often no more than 50-55 C. Tabsorbed heat = 3.5 C represents an approximated annual mean (by the brine adsorbed) temperature, during the heating season, from a 150 m deep borehole (heat source), geographically located in the Stockholm, assuming that the borehole has been in operation during a longer period and attained an converged temperature (see Akander et al. (2008) or Paper V appended in this thesis). Note; the normalisation assumes that the modifying efficiency factor () has a constant mean value within the normalised temperature interval, hence the elimination of the modifying efficiency factor in Eq. 20.

heat emitted 1.

heat emitted 2.

estimate 1.

estimate 2.estimate Norm TT

COPCOP

1 (20)

Heat source temp C

20 25 30 35 40 45 50 55 60 65

Heat emitting temp C

0 °C 2 °C 4 °C 6 °C 8 °C 10 °C

Heat source temp C

30 32.5 35 37.5 40 42.5 45 47.5 50 52.5 55

0 °C 2 °C 4 °C 6 °C 8 °C 10 °C

Heat source temp C

40 42.5 45 47.5 50 52.5 55 57.5 60 62.5 65

0 °C 2 °C 4 °C 6 °C 8 °C 10 °C

(c) Fig. 20. (a), (b), (c) Normalised change in COPestimate (as presented in Eq. 20) for different temperature intervals; the normalisation is based on the temperatures T1.emitted heat = 40 C and T1.absorbed heat = 3.5 C.

3.3 SOLAR-ASSISTED HEAT PUMP SYSTEM The basic working principle of a Solar-Assisted Heat Pump System (SAHPS) (a theoretical and hypothetical design for heating in this specific example; note, no discussion on control strategy is presented) is that solar radiation or/and heat via outdoor air convection is absorbed by a solar collector (glazed or unglazed) (Duffie and Beckman, 2006; Kjellsson, 2004). The energy, in the form of gained heat, is thereafter transported from the solar collector via the heat transfer fluid to either the: DHW, space heating, HP or thermal energy storage (see Fig. 21). The heat is distributed differently between these system parts depending on its temperature and the heating requirement. At high temperatures, the heat can directly be used for heating or preheating DHW, space or be stored for future use. If the fluid temperature from the solar collector or thermal energy storage is too low for direct or indirect use, a temperature raise is needed to make the heat useful. This is achieved by a HP, which works up the heat to a desired temperature level. If the fluid temperature coming from the solar collector is too low for all system use, then the collector is not in operation. The fundamental aim with a SAHPS is to attain higher heating or cooling COP values in comparison to regular HP systems (Kjellsson, 2004). For a detailed thermodynamic description of the HP process, see e.g. Moran and Shapiro (1993). The possibilities, benefits and build-up of a SAHPS, for heating or cooling purposes, has been studied in various projects since the 1970s; e.g. see (Kjellsson, 2004; Ozgener and Hepbasli, 2007; Hepbasli and Yildiz, 2008). These projects display a variety of system designs in various climates. They also present a range of performance results and advice/suggestions on system design, control strategy and performance. Due to differences in system complexity and application, it becomes difficult to formulate any general conclusions concerning system design, usefulness and performance (Kjellsson, 2004). The possibilities of combining solar or SAHPS with Photovoltaics (PV’s), hence attaining a PV/T unit or PV/T-assisted HP system, is discussed and studied by e.g. Van Helden et al. (2004), Hamada et al. (2001) and Huang et al. (2001). PV/T R&D, use and needs are also presented by PV-TRAC (2005). Up-to-date work within this field is being conducted in the IEA SCH Task 35 (2009). SAHPS have a variety of system build-up and control strategy complexity (depending on design), due to a combination of various components, temperature levels, thermal requirement (storage vs. usage), climate and system output (amount and duration of heating or cooling use) variations; making the task of designing and optimising these dynamic systems in terms of performance and cost demanding. The assessment of system performance from various designs and operations has in previous studies been made by computational simulations or experimental tests (Kjellsson, 2004; Ozgener and Hepbasli, 2007; Hepbasli and Yildiz, 2008). System simulations and analysis specifically focusing on Nordic system design (residential heating) is presented by: Tepe and Rönnelid (2002), Tepe et al. (2005) and Kjellsson (2004). Kjellsson (2004) discussed and concluded the importance of optimising (hence reducing) the use and running time of circulation pumps and other energy consuming auxiliary components, in a SAHPS (for heating) coupled to a borehole. The energy consumption by these components may reduce the efficiency and overall system performance, to an extent that the benefit of this particular system solution is jeopardised.

Fig. 21. A drawing of a hypothetical SAHPS design for heating in order to graphically exemplify: the system, its components and interactions in a conceptual way. The assumed HP has a built-in DHW heater. Note that the hypothetical system drawing is made without regards to practical issues and that all components needed for an operational system are not included. Projects aimed at developing and using dual-purpose collectors that integrate with the building to form its roof have also been carried out, e.g. Dalenbäck (2002), the EU projects EMA (Façade and Roof Integrated Solar Collector) (EMA, 2009) and ENDOHOUSING (Endothermic Technology for Energy Efficient Housing in the EU) (see chapter 5 and Virk, 2008).

Space heating

Hot water

HEAT PUMP

Thermal energy

storage / source

Solar collector

4-way-valve

Heat exchanger

Cold water

4 GENERAL DESCRIPTION ON DURABILITY OF THERMAL SYSTEMS

An overview of R&D projects and published papers/reports in this field of research shows that the extent of research and knowledge is sparse; regarding durability and lifetime performance analysis of solar collector combined or thermal/energy systems/technologies in general, showing that further studies are needed. Bankvall et al. (1986) discussed ‘relatively early on’ the need of durability knowledge and assessment of building services and energy technologies generally utilised in buildings, as well as stressing a number of R&D needs within this specific area. A variety of reports have also been published by the Swedish R&D organisations such as Elforsk, Värmeforsk and Svensk Fjärrvärme, with primary focus on durability and reliability methodologies/assessments of energy technology/system constructions and plants. Many of these reports can be downloaded from their respective internet home pages: Elforsk (2009), Värmeforsk (2009) and Svensk Fjärrvärme (2009). 4.1 SOLAR COLLECTORS AND HEAT PUMPS UTILISED IN BUILDINGS Studies on HPs and SAHPSs have during the years been specifically focused on investigating their energy and economical ability. There have been some sparse studies of how HPs and SAHPSs perform over time, e.g. Marcic (2004) and Huang (2003). These tests and surveys consisted of long-term monitoring of the system performance; - no analysis on system degradation was made. General surveys have also been conducted on HP and solar collector durability, e.g.: The insurance company Folksam has presented statistics on reported (to their

company) HP damages in Sweden (Folksam, 2009). The statistics from Folksam show that many of the damaged HPs were relatively newly installed units. 73 % of the reported damages during the year 2007 were HP units that were less than 5 years old.

Considering regular solar energy systems, international surveys show that about 60 %

of all active solar energy systems have experienced some problems during operation (Wennerholm, 2003). Malfunction of solar collectors are due to erroneous manufacturing, installation or freezing. Other problems relate to degradation due to various load exposures (solar radiation, temperature, wind, rain/humidity, snow and airborne pollutants) as a result of outdoor placement and in-service use.

The Swedish national testing and research institute (SP) has since the introduction of

solar heating in Sweden been involved in durability studies of solar collectors. They have performed nationwide inspections of collectors and written several reports, see Wennerholm (1994). The aim of these inspections was to get a general view of the status which the collectors are in at a specific time with emphasis on durability and reliability. A similar study as those carried out by SP was made by Wennerholm (1994). The objective was to examine and document the conditions of solar collectors in various systems.

Scientific studies related to durability and lifetime performance analysis/modelling of solar energy applications have mainly focused on some solar energy materials and not solar energy

technologies/systems in general. Extensive research on solar collector material durability has been made (as also noted in section 2.2.3) in the IEA Task X (Task 10) “Solar Materials Research And Development” of the International Energy Agency Solar Heating and Cooling programme (Carlsson et al., 1994). The work was organised as a case study in which commercially available selective absorber coatings were examined. These coatings were used in glazed flat plate solar collectors for attaining DHW. An accelerated test procedure was developed to test the lifetime performance of the absorber coatings (ISO/CD 12592.2). In order to investigate the effects of selective absorber coating degradation on the annual performance of a DHW collector system, computer simulations were made by Hollands et al. (1992) within the Task 10 study. The simulations were meant to determine the relationship between the change in solar absorptance and thermal emittance, at a specific decrease in annual solar fraction of the DHW collector system. How absorber coating degradation affects the energy performance of other combined solar energy technologies/systems was not studied. A similar study was reported by Degelman (2008); on measured performance of a residential solar water heating system, over a period of 22 years. The system was also modelled in order to incorporate the performance degradation over that period. Other studies on the optical durability of reflectors for solar energy applications have also been conducted, e.g. (Brogren et al., 2004, a) and (Brogren et al., 2004, b). Durability studies on flat-plate solar collector covers have also been conducted, e.g. see Waksman et al. (1985) and Köhl et al. (2005). A continuation and further development of Task 10 is Task 27, Performance, Durability and Sustainability of advanced windows and solar components for building envelopes. The objectives of Task 27 in the Solar Heating and Cooling Programme of the IEA are to determine the solar, visual and thermal long-term performance of materials and components, e.g. (Carlsson et al., 2004, a); see also related journals e.g. (Carlsson et al., 2004, b) and (Köhl et al., 2005). Worth noting is that the Carlsson et al. (2004, a) report present approaches on Failure Modes and Effects Analysis (FMEA) of solar components. As discussed in section 1.3, directives, laws and regulations of today claim performance-based requirements of construction works, of which the working life is an essential part. These also lay emphasis on construction works to fulfil the set requirements as an assembled system, and not solely on the basis of individual parts. The main issue on lifetime performance of thermal/energy systems/technologies (as discussed in section 4.1) is how and to what extent, performance reduction in individual materials and components influences the overall system performance (see Fig. 22), as the essence of thermal/energy system sustainability lays in system performance. The bridging of material degradation (in relation to some performance characteristics) to system performance (see also section 2.5) is vital and may be sought-after as presented by Hollands et al. (1992), through system stimulations. Changes in vital (identified) system performance parameters are put in relation to system boundary conditions, thereby evaluating the interrelated affects of parameter change in relation to the overall system performance. The outcome of such a system parameter analysis may result in mathematical expressions that correlate these parameter changes with altered system performance. This brings to the attainment of facilitating tools that tie material degradation, affecting parameter change, to altered system performance, which may also be used as requirements criteria. The impact of change in optical and thermal properties on flat plate solar collector performance has been studied by Hellström et al. (2003).

Fig. 22. A flow chart with figures schematically representing the course of events and interaction of degradation environment, material degradation and thermal/energy system and building performance reduction.

Degradation environment (outdoor exposure and in service use)

Solar collector

Material (absorber coating) degradation

Reduction in solar radiation (energy) absorption

Reduction in solar collector performance (energy)

Reduction in building performance (energy)

Indoor climate

Reduction in system performance (energy)

Space heating

Hot water

HEAT PUMP

Thermal energy

storage / source

Solar collector

4-way-valve

Heat exchanger

Cold water

5 THE EU PROJECT ENDOHOUSING The EU project Endothermic Technology for Energy Efficient Housing in the EU (ENDOHOUSING) Project No: NNE5-2001-00565 was launched June 2003 and officially ran to May 2006 (Virk, 2008). ENDOHOUSING was a demonstration project for exploring the potentials of a particular SAHPS design, that combines components available on the market, for providing thermal energy to meet full space heating/cooling and hot water requirements for domestic houses in different regions of the EU throughout the year; thereby assessing the feasibility of designing and realising a full-scale and almost commercially available SAHPS. The only component that is not commercially available is the solar collector. It was developed and designed as a roof-integrated USC named the Endopanel. The objective was to accomplish USC’s that propitiously blend into their surroundings (different shapes and colours, see Fig. 23) thus preventing an ‘add on’ appearance and having a dual and symbiotic function (heat absorbing component and roofing). The USC consists of an extruded aluminium profile that comes in two shapes, flat and bold rolled (see Fig. 23). After extrusion, the ends are sealed and in-/outlet pipes are attached by welding. Thereafter, the panels are painted with a polyester powder coating. Each profile has a fixed width (0.22 m) while the length can vary up to a maximum of six meters. Feet enable fixation onto the roof and folds allow interlocking between adjacent panels. The heat transfer liquid flows through the panel in one homogenous direction, where each duct makes up an individual parallel flow streak (see Fig. 24 (b)). From a thermal perspective, the choice of using an USC is based on its varying working abilities. Despite that an USC produces lower fluid temperatures than a glazed collector (Kjellsson, 2004), it can absorb and emit heat from and to the ambient via: convection, moisture condensation and long wave (IR) radiation, widening and prolonging its thermal use and being able to emit excess heat produced by the HP when the system is in cooling mode (see Fig. 25 (b) and Virk (2008)).

(b) Fig. 23. Demo samples presenting the flat panelled (a) and the bold rolled (b) roof integrated USC from the ENDOHOUSING project.

Five demonstration sites (Endosites) were established and equipped across the EU from latitudes 35°-62° (Mediterranean to Nordic climates). These systems were installed in buildings such as ordinary houses, dwellings and office buildings that are situated in Cyprus, southern and northern Italy, in central Germany and Sweden (Sandviken, see Fig. 24 (a)). These five installed systems are based on the same concept (Virk, 2008), with some modifications made to adjust and optimise performance to the prevailing local climatic conditions.

(b) Fig. 24. A picture of the roof-integrated flat panel USC, installed at the Swedish demonstration site in Sandviken (a), and a drawing showing the ENDOHOUSING flat panel USC (b). The basic concept of the ENDOHOUSING SAHPS is to have two thermal storages with different temperatures, named cold and hot store consisting of storage vessels (Virk, 2008). These storages are intermittently charged and discharged with heat (on daily basis) by the USC, HP or space heating circuit (see Fig. 25). The HP is a commercial product for domestic heating purposes, normally coupled to a borehole or Ground Heat Exchanger (GHE). This particular HP has a built-in tank for DHW generation, Circulation Pumps (CPs) (cold and hot side) and Auxiliary Heat (AH) (electricity backup), commonly used in Sweden (Scandinavia); Sweden being one of the largest ground-coupled HP markets in Europe (Kjellsson, 2004; Eriksson, 2004).

(b) Fig. 25. System drawing of the ENDOHOUSING SAHPS installed in Soest, Germany, which represents the original system concept (Virk, 2008). Figure (a) presents the system in heating mode. No direct solar heating or preheating by the USC is made in the German system. Figure (b) presents the system in cooling mode. Heat produced by the HP is emitted from the USC. No DHW is produced in the German system.

5.1 THE SWEDISH DEMONSTRATION SITE The Swedish demonstration site is located in Sandviken. The house, from the 1920’s (see Fig. 24 (a)), does not offer favourable conditions for low energy use nor utilisation of a SAHPS (which presents an intriguing challenge for the system), as it is: Poorly thermally insulated leading to large heat losses, power requirement and high

supply temperatures. The heat distribution system has few radiators; hence the supply temperature must be

high in order to emit the required heat (not optimal for HP COP (see section 3.2.2). The roof is oriented to the east and west (the USC’s are placed eastward). No roof

surface is exposed to direct solar radiation during the entire day, limiting the potential of absorbing global solar radiation. Surfaces oriented towards the south have the highest exposure of direct solar radiation (Kjellsson, 2004; Duffie and Beckman, 2006) in the northern hemisphere.

The system was installed during the autumn to winter in 2005-2006. The main parts are: USC’s: 39 Endopanels which are 4.95 m in length, with a coverage of ~42.5 m2 (see

Fig. 24). Heat pump: IVT Greenline HT Plus 9C, thermal output 8.4 kW (see Fig. 27 (b), IVT

(2009)). Energy storage: IVT compact Ground Heat Exchanger (GHE) (see Fig. 27 (a), IVT

(2009)), 18 modules in two circuits, ~52 m2 effective module area, placed horizontally at a depth of ~1.5 m in the ground.

USC and energy storage fluid: Thermera, the main substance is betaine

‘environmentally friendly’; temperature range goes from -15C to +110C. (Thermera, 2009).

Valves (main valve see Fig. 26), CPs (see Fig. 26), monitoring and control equipment

(see Fig. 28). Electrical power use for CPs: GHE circuit 250 W, USC circuit 100 W. In comparison to the original ENDOHOUSING system concept, this system was adapted for Nordic climatic conditions and use, since heating is the predominant requirement. The heating season is characterised by low solar radiation and outdoor temperatures. Intermittent operation on daily basis for recharging the cold store, see Fig. 25 (a)), is not possible when the heating requirement is considerably higher than the heat input into the cold store. The adaptation of the Swedish system consisted in replacing the cold store vessel with a seasonal heat storage, a GHE. It charges the ground (via the USC) with thermal energy during late spring, summer and early autumn months (low space heating requirement and solar energy in abundance), see Fig. 26 and 27 (a). Thermal energy is extracted during the heating season, when there is no available solar/ambient energy absorbed by the USC, though intermittent recharging may occur upon the presence of warm winter periods.

•Heat •exchanger

•Roof circuit

•Radiator circuit

•Hot

•store•Heat

•pump

•4-way valve

•Compact ground

•heat exchanger

•Tap w ater•Heat •exchanger

•Roof circuit

•Radiator circuit

•Hot

•store•Heat

•pump

•4-way valve

•Compact ground

•heat exchanger

•Tap w ater

Fig. 26. A system drawing of the Swedish Endosite which schematically presents the flows and system components and operation. The CP’s next to the HP are actually built in the HP. Besides recharging the heat storage (via the USC), the overall temperature of the ground and fluid temperature to the HP evaporator is raised, hence increasing COP in comparison to a traditional non charged ground collector or borehole (commonly used as a heat source in Swedish HP installations (SVEP, 2009)). This design is based on the roof circuit (USC) charging the ground or directly raising HP evaporator temperatures (see Fig. 26). There is neither direct heating nor preheating with the USC of the DHW or space heating, as it was anticipated that the ‘direct useful’ heat or temperature level obtained from the USC is insufficient most part of the year. During the summer season, there will be occasions when the heat and temperature level from the USC is sufficient for preheating DHW. But, the energy savings this will render, compared to only running the HP, is seen as to low (within the scope of the ENDOHOUSING project) in view of a more complex and costly system design. Normal energy usage of DHW during the summer is for an average Swedish family about 2000 kWh (Kjellsson, 2004). At the Swedish Endosite, DHW consumption was scheduled to simulate ‘normal’ residential behaviour, since there were no occupants at the time of system installation. DWH was drained twice per day (morning and evening) to resemble daily energy usage of an average Swedish family, ~14 kWh (Kjellsson, 2004). The SAHPS was set to deliver space heating for obtaining an indoor temperature of +20C. Internal heat sources, such as electric apparatus and human beings, were not simulated.

(b) Fig. 27. (a) The GHE installed for thermal energy storage in the ground (via the USC) and to be used as an HP energy source. (b) The basement at the Swedish site where the HP is installed and connected to the rest of the SAHPS (see also Fig. 26). The system consists of three main circuits: the GHE, the roof (USC’s) and the radiators (space heating), see Fig. 26. As previously noted, the circuit fluid in the USC’s and GHE (thermal energy storage) is Thermera (Thermera, 2009). As mentioned previously, the HP used in the project is a market product which is designed for domestic heating purposes using a borehole or GHE as energy source. This particular HP has a built-in tank for DHW production, CPs (cold and hot side) and Auxiliary Heat (AH) (electricity), as customary in Scandinavian (Swedish) installations. The sole component controlling the evaporator inlet temperature and routing of thermal energy to and from the GHE is a 4-way-valve. It acts both as a flow router and mixing valve (controlling temperature). Nordic ground-coupled HP’s are optimised for borehole and ground collector installations (temperatures). The maximum allowed inlet evaporation temperature is +20C, but often recommended to be +15C (Kronström, 2009).

The 4-way-valve is set to operate as presented in the following scenarios: The USC’s charges the ground with thermal energy, simultaneously as the HP is in

operation. The 4-way-valve mixes the fluid entering the HP evaporator to the maximum temperature of +15C. If below +15C, the flow is directly routed to the evaporator. The same scenario also applies when the USC’s are not charging the ground.

The USC’s charges the ground when the HP is not in operation. The 4-way-valve

bypasses the flow directly to the GHE. The USC roof is in operation (throughout the year) as long as the fluid temperature from the USC is higher than the fluid temperature from the GHE. There is an exception - if the outgoing USC fluid temperature is ± 0 C (after heat exchange with the ground circuit, see Fig. 26) while the outdoor air has a relative humidity 70 % and temperature ± 0 C, heat absorption is prohibited to avoid moisture condensation and freezing on the USC surface. The control of CPs running time was not optimised within the scope of the ENDOHOUSING project. The CPs for the roof (USC), ground (heat exchanger) and heating (radiator) circuit (see Fig. 26) were set to run continuously. On/off flow in the roof circuit was controlled by a magnetic valve. The radiator circuit even has continuous flow during the summer season; a common operational scenario in regular Swedish radiator circuits. Besides the previously mentioned CPs, the HP also has two built-in CPs, as graphically presented in Figure 26. The operation of these is entirely controlled by the HP. When the HP is in operation, the CP at the cold side (evaporator) is automatically set to run. The CP at the hot side (condenser) is only running when there is a space heating demand, mainly when the HP is running but also if the AH is on. The full-scale test of the Swedish ENDOHOUSING SAHPS commenced in February 2006 and is still ongoing, although the ENDOHOUSING project officially ended in May 2006. In order to be able to assesses and analyse the system and its various component performances, monitoring and data logging was/is conducted. Several temperature and fluid flow measurements were/are performed throughout the system, as well as HP electrical use, local climate monitoring and indoor temperatures (see Fig. 28). The fundamental system monitoring strategy was to obtain absorbed or emitted heat and electrical power use in time of the various system parts: USC, GHE, HP, DHW and space heating. The sampling rate is 1 minute.

Fig. 28. A system drawing of the Swedish Endosite SAHPS, showing where: system (temperatures and flows), outdoor climate (temperature, solar radiation, relative humidity and wind speed), indoor climate (temperature) and HP (electrical power use) parameters were/are measured. 5.2 SYSTEM PERFORMANCE EVALUATION METHODOLOGY Efficiencies are defined in various ways, though the main purpose is to establish the net useful energy (upgraded energy) delivered from the process, in relation to purchased energy that has been supplied to the system. In terms of HPs and HP systems, there are mainly two types of efficiencies which are commonly used to quantify and evaluate performance, e.g. see Kjellsson (2004) and Tepe et al. (2005). These are: Coefficient of Performance (COP) and Seasonal Performance Factor (SPF). COP is a momentary entity that is somewhat constant in time when the HP unit is in operation, if and only if temperatures in the system are constant, i.e. the system is operating at steady-state. However, when the HP unit is in operation, the conditions (temperatures) are liable to change, hence affecting COP values. Eq. 21 presents the HP COP as traditionally defined:

evaptrad HP E

As can be see in Eq. 21, the traditional HP COP is momentary or based on a steady-state HP operation, where the input is generally in Watts. Furthermore, the HP is defined with system boundaries set next to the HP unit (traditionally defined as: evaporator, compressor, condenser and pressure valve), whereas the SPF comprises the entire system in time. The COP only takes into account electricity supplied to and heat delivered from the HP unit

(compressor and condenser), whereas SPF involves other energies that is actively supplied to and delivered from the system, such as energy (electricity) to CPs and control units. A vital difference is also that SPF also considers energy (electricity) supplied to the system, though the HP unit is in stand-by mode (the compressor is not working at the time). In general, SPF may give values which are lower than those of COP. For example, electricity for running CPs in order to maintain system fluids flows, e.g.: roof (USC), GHE and radiator circuit, will appear in SPF whether or not the HP unit is running, thus reducing the value of SPF. However, SPF may also give higher values than COP during favourable conditions. If the temperature from the USC is sufficiently high, then the thermal energy can directly be used for heating or preheating DHW or space heating, thus increasing the value of SPF as the HP is not in operation although heat is delivered. Note, this operation scenario is not relevant for the Swedish ENDOHOUSING SAHPS. The analysis performed on the SAHPS (see also Paper IX appended in this thesis) is focuses on performance of the HP and total system within heating applications; see Eq. 22-24. The SPFHP can be seen as the upper limit of performance in this SAHPS.

AHCPs HPcomp

tot HP

output tot HPHP EEE

QSPF (22)

Eq. 22 can be rewritten and expressed in terms of monitored variables such that

AHCPs HPcomp

DCWDHWpDHWHPHSHSHPpHSHPHP EEE

TTctmTTctmSPF

SPF for the system is in energy form described by Eq. 24, where

GHE CPUSC CPtot HP

tot SAHPS

output tot SAHPSSAHPS EEE

QSPF (24)

5.3 LONG-TERM SYSTEM PERFORMANCE RESULTS SAHPS operation, monitoring and data logging commenced in February 2006 at the Swedish demonstration site. At the time, data logging from all Endosites across Europe were stored at a central server in Germany. Although the ENDOHOUSING project officially ended in May 2006, data logging from the Swedish Endosite continued until ~October 2006. Thereafter, storage in the central server was terminated (due to end of the ENDOHOUSING project). Local data storage was not established until February 2007, but has continued and is still ongoing (at the time of writing this doctoral thesis). The system performance data presented in this section is from the period of 2006(feb)-2006(sep) and 2007(feb)-2008(feb), with exception for the GHE. The figures show the relative system performance SPFHP and SPFSAHPS (according to Eq. 22-24), and the absolute temperature variations of the GHE on annual and monthly basis. Paper IX appended in this thesis, presents an ingoing system performance analysis of the Swedish Endosite.

jan feb mar apr may jun jul aug sep oct nov dec jan feb

2006 2007 - 2008

jan feb mar apr may jun jul aug sep oct nov dec jan feb

2006 2007 - 2008

2006 (feb-sep) 2007 (feb) - 2008 (feb)

HP SAHPS

(c) Fig. 29. (a) Annual variation in SPFHP per month. (b) Annual variation in SPFSAHPS per month. (c) Annual SPFHP and SPFSAHPS.

Significant annual variations in HP and SAHPS performances are displayed in Figure 29 (a) and (b). The annual variations in SPFHP presented in Figure 29 (a) are due to varying outdoor temperatures and solar radiation, hence heating requirement. The total heating requirement results from both space heating and DHW, so the share of total heating that each represents will vary throughout the year. Since the annual DHW is quite evenly distributed, minutely affected by outdoor temperature variations, the change in total heating requirement/output is thereby due to space heating. These variations will affect both the SPFHP and SPFSAHPS, since a change in total heating requirement shifts system heat output temperature levels (DHW vs. space heating). The HP condenser temperature is commonly for DHW significantly higher than for space heating. Besides annual SPF variations, there is a significant difference between SPFHP and SPFSAHPS. The overall reduction in SPFSAHPS is primarily due to the power (electrical) use of system CPs (see Fig. 26 and section 5.1); showing the importance of optimising (hence reducing) the use and running time of system CPs and other energy consuming auxiliary components (as also discussed and concluded by Kjellsson (2004)), in order to obtain as efficient SAHPS performance as possible. Data processing of the series representing the full year period of 2007(feb)-2008(feb), presented a HP and total SAHPS performance of: SPFHP=2.85 and SPFSAHPS=2.09 (see Fig. 29 (c)). It is argue that with an optimised SAHPS control and operation strategy, additional use of CPs and energy (electricity) could be vastly reduced, hence attaining SPFSAHPS value that is equivalent to the SPFHP. Regular ground-coupled HP systems display an annual mean value of COP3 for residential heating in Swedish (Nordic) conditions (STEM, 2009). Having this in mind and considering that the Nordic (Swedish) ENDOHOUSING SAHPS has not yet been properly optimised/designed and installed in an appropriate house (see section 5.1), the SPFHP=2.85 is considered as being a success.

(b) Fig. 30. (a) incoming and outgoing GHE fluid temperatures in 2006. (b) incoming and outgoing GHE fluid temperatures in 2007–2008. In November 2007, the USC fluid froze causing the panels to burst. Due to previous leakage in the coupling between the manifold and the Endopanels, the USC circuit was continuously refilled with water during the spring and summer, to the extent that the antifreeze protection of the fluid was not adequate. A planned refilling of the USC circuit with new antifreeze protected fluid was unfortunately delayed and resulted in damage. This meant that the ground heat storage could no longer intermittently be charged with heat. This was unfortunate for the SAHPS, but an opportunity to analyse and compare the behaviour of the GHE (ground heat storage) as the system is still operational. Comparing Figure 30 (a) and (b) (the 2006 and 2007 series), shows that the ground heat storage displays similar thermal behaviour. By comparing the 2008 series with the rest shows a considerable temperature reduction, especially during the summer period. The comparison shows that the period ~March to ~October has a significantly lower mean ground temperature, due to the absent thermal charging of the ground. Although the incoming fluid (hence ground) displays a significantly higher temperature during the summer period, the temperature rapidly declines during the autumn period to the same level as for the uncharged period of 2008, corresponding to the beginning of November. This indicates that the present ground heat storage design (at the Swedish Endosite) e.g. concerning: ground depth, soil type, surface area and GHE configuration, is not capable of extensive seasonal heat storage. In order to make an extensive analysis of improved thermal storage capacity, a relevant model of the GHE and its surroundings has to be developed. At present time, such a model is not readily available. As the GHE is located in soil, the thermal storage process is not only described by ordinary heat transfer, but is also significantly dependent of moisture transport (from precipitation, water tables, surrounding soil, snow layers, etc. affecting thermal parameters) and phase change (vapour/water/ice). The influence of moisture can be noticed in the fact that the fluid temperature in the ground is below zero, but quite constant for about four to five months. The effects of moisture will make the GHE model complex and at the same time it has to be suitable in system simulations, hence restricted amount of computational power and time.

6 LONG-TERM THERMAL PERFORMANCE MODELLING OF A BOREHOLE

The section presents the methodology for thermal RC-network modelling of building components. It shows a procedure that is meant to bridge the long-term component performance (thermal in this case) to performance of the system, by deriving a suitable model for these types of simulations. This provides the possibilities for assessing the performance-over-time with a low computation power and time, giving an adequate tool for SL planning. The thermal RC-network methodology is as flows: The time dependent heat-equation is expressed for one dimension as presented in Eq. 25.

For harmonic periodic boundaries, the temperature and its derivate can be expressed as in Eq. 26 and 27.

)(ˆ~ tieTtT (26)

TaTiTi

The solution of the heat equation in Eq. 27, in a heat balance between two points, 0 and 1 (inlet and outlet), for a homogenous layer construction (material), can be expressed as a frequency dependent matrix Eq. 28 (Carslaw and Jaeger, 1959; e.g. Jóhannesson, 1981), see also Figure 31.

where the expressions of the transformation matrix are: ilkA 1cosh (29)

ilkikC 1sinh1 (31) ilkD 1cosh (32) k in the expressions above is defined as:

The solution presented in Eq. 28, can be reorganised to calculate the heat fluxes when the temperatures are known at the two points, Eq. 34, see also Figure 31.

The expressions of the transformation matrix (Eq. 34) are defined as: BDE (35)

BBADCF 1 (36)

BG 1 (37)

BAH (38)

The solutions presented in Eq. 28 and 34, represents the transformation matrix for one layer. When having a multilayer construction, one simply has to multiply the transformation matrixes (for each layer) with each other, and attain a resulting matrix which transforms the known values at some ambient boundary point to the other (Akander, 2000). The dynamic performance of a material or construction (response), may be defined by using the concepts of admittance and transmittance (Jóhannesson, 1981), which are the relationships between temperature and heat flow oscillations at the boundaries, Eq. 39, 40 and 41. This can be visually presented as Figure 31 (Akander, 2000).

Fig. 31: The implication of admittance and transmittance (Akander, 2000).

Admittance

Transmittance

The admittance can be defined as a measure that describes heat exchange between a system and the ambient (at one side, see Fig. 31), hence the relation of temperature and heat flow. If the temperature of the opposite side of a construction or material is constant (no fluctuation), the admittance can be defined for the specific side as presented in Eq. 39 and 40.

QY (39)

QY (40)

The transmittance is defined in a similar way, but is dependent on the temperature and heat flux of the obverse sides, Eq. 41.

QTD (41)

After attaining the dynamic performance knowledge of some construction (in the frequency domain) the main task is to transform the construction’s dynamic thermal performance into a suitable RC-network configuration, for simulation purposes in the time domain (Jóhannesson, 1981; Akander, 2000). This procedure is called the -RC transform, and the advantages of this modelling method is that it establishes simplified yet accurate thermal models, which require less computing power and time compared to traditional finite difference/element models. RC-networks are suitable for system simulations. The resistances (resistors) and capacities (condensers) in a RC-network configuration are modelled with a matrix in similarity with the transformation matrix procedure in Eq. 28 and 34. A single resistance and capacitance is modelled in the following way (Jóhannesson, 1981; Akander, 2000):

BA (42)

A combination of resistances and capacitances in a RC-network configuration will give a matrix that is a product of the resistive and capacitive parts in the configuration. As an example, the simplest RC-network configuration for a finite body, the so-called T-configuration, is presented in Figure 32 and Eq. 44.

Resistance

Capacitance

Fig. 32. The T-configuration which represents the simplest RC-network configuration for a finite body (Akander, 2000).

A key concept in the -RC transform modelling approach, is the notation named active (or effective) heat capacity (Jóhannesson, 1981; e.g. Akander, 2000). The active heat capacity is the quantification that corresponds to the part of the total heat capacity of a (e.g. building) material or construction, which actively participates in a dynamic heat exchange with the ambient; as expressed in Eq. 45.

0Y (45)

By attaining this knowledge for a certain frequency interval (the interval which the component or material will experience in its specific area of use), will minimise and optimise the thermal capacity which has to be regarded, thereby attaining a yet simplified model as the dynamic mass has undergone a model optimisation. The active heat capacity is based on the admittance and is expressed for the simplest RC-network configuration as Eq. 46 and 47 (see Fig. 33).

YrealR (46)

Fig. 33. An RC-network configuration in its simplest form for a semi-infinite body, which represents the thermal mass in the active heat capacity (Akander, 2000). When obtaining the values of the single resistance and capacitance in the simplest RC-network configuration, the total value of these two parameters has to be distributed in a (chosen) more elaborate RC-network configuration, set to model some component (see Akander (2000) and Paper II (Stojanović and Akander, 2005) appended in this thesis). In order to attain the optimal distribution, the network is optimised in a manner of an iterative procedure, so that the thermal performance of the RC-network is as close as possible to the analytical solution for a chosen number of frequencies. The deviation between the optimised RC-network and the analytical solution is estimated by using Eq. 48 (Akander, 2000). A finite difference or element method with complex temperature boundaries can also be used in the -RC transform modelling approach, for complicated or multidimensional geometries (Mao, 1997; Weber, 2004).

i ianalytical

iionconfiguratRCianalytical

6.1 THE BOREHOLE MODEL This above presented thermal modelling approach and procedure, and the further developed MEM-method (Schmidt, 2004), was utilised when a borehole model was developed; as presented in Paper II (Stojanović and Akander, 2005) appended in this thesis. As a HP system equipped with a borehole is in operation, heat is discharged from the borehole. In time, the borehole cooling causes the ground temperature to decline. As a result of this effect, the gained temperature from the borehole decreases, resulting in lowering the efficiency of the HP system, which will directly affect its economic performance. These changes require a performance-over-time assessment for boreholes due to their intended long-term utilisation as a component in HP systems. To be able to simulate a regular HP or e.g. a SAHPSs annual energy performance, as well as their long-term performance, due to e.g. borehole temperature variations, requires large amounts of computing power and time. This makes it beneficial to have system component models that are simplified yet accurate. The procedure for deriving the borehole model developed in Paper II is given in the flow chart presented in Figure 34.

Fig. 34 A flowchart presenting the long-term thermal performance modelling of a borehole for heat extraction. The borehole modelling presented in Paper II was performed on a single borehole for heat extraction, which is filled with ground water and equipped with a U-shaped pipe. This is the most common design in Swedish installations. The modelled borehole is chosen to have a diameter of 0.140 m. The heat fluxes are seen as being one-dimensional and perpendicular to the vertical borehole. It was also assumed that the ground temperature increases proportionally with the depth in undisturbed ground. This provides the possibility to attain a representative mean-temperature of the whole borehole length, which is practical to use when calculating heat extractions from a borehole. Further assumptions made in the model are that there is no natural ground water flow through the borehole. The fluid flow temperature is assumed to increase proportionally with the flow path. This assumption can be made for small temperature rises at relative high fluid velocities, see Claesson et al. (1985), which is the case in most residential HP installations. The temperature of the solid rock (see Fig. 35) is also assumed as changing linearly along the borehole, as a result of heat extractions. Figure 35 presents an illustration of the borehole modelling procedure and the utilised RC-network configurations. The U-pipe model (star resistance network) was developed by Claesson et al. (1985), and set to model this part of the borehole. The solid rock part was modelled by using a modified half 5-node RC-network (semi-infinite body model), originally developed by Akander (2000) and also utilised by Schmidt (2004).

Solid construction model: modified half 5-node RC-

network

Thermal performance simulation of the borehole in

time domain

U-pipe heat/cold carrier flow model: star resistance

network

1-D analytical ground model: frequency domain

Optimisation of the RC-network parameters for time

domain calculations

Fig. 35. The procedure and RC-network configurations used in modelling the long-term thermal performance of a heat extracting borehole. The whole RC-network configuration, set to model the long-term thermal performance of a heat extracting borehole, is presented in Figure 36. T5 in the network is set as a constant temperature, as the borehole perimeter (for a certain time period, see Paper II) is undisturbed by the heat extraction. All the other nodes are active and dynamically working in the time dependent model.

Fig. 36. The RC-network configuration, derived to model a heat extracting borehole equipped with a U-pipe.

R 12 T f2

T f1 Q 1

Borehole RC-network

U-pipe resistance network Semi-infinite solid body RC-network

U-pipe

T f1Q 1

Admittance

Modified half 5-node RC-network (semi-infinite body model)

Star resistance network (U-pipe model)

Borehole

Solid rock

The temperatures Tf are affiliated to the U-pipe inlet resp. outlet fluid flow. The encircled temperature T1 is the borehole mean-length wall temperature. The figure below presents a long-term simulation with the above presented borehole model, and the same: input values, boundary conditions and assumptions as presented in Paper II, except for the borehole length and annual heat extraction. Figure 37 shows the change in borehole mean-length wall temperature (T1), for a time period up to 50 years, for different borehole lengths. The total annual energy output from the borehole is set to 10 MWh, which has a base load of 1.5 MWh and an annual variation.

0 10 20 30 40 500

Annual variation, 200 mMean annual temperature

a. Mean-length temperature variation for a 200 m deep borehole for up to 50 years. Starting mean-length temperature is 7 ºC.

0 2 4 6 8 100

b. Mean-length temperature variation for a 200 m deep borehole for up to 10 years. Starting mean-length temperature is 7 ºC.

0 10 20 30 40 500

c. Mean-length temperature variation for a 150 m deep borehole for up to 50 years. Starting mean-length temperature is 6.5 ºC.

0 2 4 6 8 100

d. Mean-length temperature variation for a 150 m deep borehole for up to 10 years. Starting mean-length temperature is 6.5 ºC.

0 10 20 30 40 500

e. Mean-length temperature variation for a 100 m deep borehole for up to 50 years. Starting mean-length temperature is 6 ºC.

0 2 4 6 8 100

f. Mean-length temperature variation for a 100 m deep borehole for up to 10 years. Starting mean-length temperature is 6 ºC. Fig. 37. (a) to (f): Long-term borehole simulation results. These simulation results presented in Figure 37, show how the use of a derived long-term performance model is utilised in analysing and assessing the performance-over-time for a thermal/energy system component, in this case a borehole at different borehole lengths. As presented in Figure 22, the change in a component performance affects the total system performance.

If used in a system simulation, the change in borehole mean-length temperature can be connected to altered system performance, e.g. HP COP or system SPF. Thereby using the simulation results at a design stage (of e.g. a HP system) to decide (optimising) the adequate borehole depth, based on the set system performance requirement, within a certain SL. In general, elaborate thermal analysis and modelling of ground/duct heat storage and extraction, has been performed by e.g. Claesson et al. (1985), Hellström (1991) and Nordell (1994). One of the most advanced (generally agreed upon) borehole models has been developed by Hellström et al. (1996), and is currently available as a component model in the solar system simulation software TRNSYS. 6.2 BOREHOLE COUPLED HEAT PUMP SYSTEM PERFORMANCE MODEL A further development and application of the RC-network borehole model, as presented in the previous section, is to simulate long-term HP system performance (as presented in Paper V (Akander et al., 2008) appended in this thesis). The borehole coupled HP system model, considers a Borehole Heat Exchanger (BHE) that is under the influence of a building which has a defined energy requirement. Given the energy requirement of the building, this method will calculate heat extraction and efficiency of the system. In this study, the resolution of input data is on a monthly basis. The efficiency of a HP is often characterized by the COP, Eq. 49, which indicates the rate of heat flow delivered from the HP in relation to the rate of energy flow (electricity/work) supplied to the process. Within the study, the COP was defined on monthly basis as presented in Eq. 49.

heating

monthHP E

Future more, in order to model the HP COP as a function of system temperatures, the COP was defined as the COPestimate (see also section 3.2.2), Eq. 50.

evapcond

condestimateHP TT

TCOPCOP

month (50)

Since temperatures within the HP process seldom are measured, these are within this work estimated on basis of statistics from products (Forsén, 2007). The refrigerants evaporation temperature (Tevap) is assumed to be evapT = 4 K less than the mean temperature of the brine

(borehole fluid, which is calculated with the borehole model –see previous section and Paper II (Stojanović and Akander, 2005) appended in this thesis) in the evaporator of the HP:

evapBh

outBhevap T2

. The refrigerants condensation temperature (Tcond) is in turn

assumed to be condT = 1 K higher than the mean temperature of the supply fluid for Space

Heating (SH) or DHW, in the condenser of the HP: 2

TTTT DHW)or (SH

outDHW)or (SHcondcond

outBhT and outDHW)or (SHT denotes the temperature of the borehole fluid (brine) and supply fluid

heating exiting the HP evaporator respectively condenser. Tevap and Tcond are assumed to be

constant during a steady state HP cycle. The Carnot’s modifying efficiency factor ( ) is assumed to be constant in time. By solving the set of equations above, Eq. 49 and 50 (here on a monthly basis) are obtained which gives the relationship between the heating requirement and the heat that is extracted from the BHE, such that:

condoutDHW

condoutSH

SHevapoutBhDHWSHextBh TT

QTTQQQ

outBhinBhpBhextBh TTctmQ (52)

The difference between heating requirement and the extracted heat corresponds to energy that is supplied to the HP process. Note the role of the evaporation temperature, here represented by evapoutBh TT . When the temperature in the BHE decreases over time,

outBhT will also

decrease and render a reduced heat extraction. This, in turn, means that the heating requirement will be fulfilled by increased use of HP compressor energy and/or auxiliary energy. Heat extraction from a BHE will in time reduce temperatures of the surrounding ground. In order for the cold carrier fluid to absorb heat, its temperature must be lower than that of the ground and it is at this lower temperature that the HP will obtain heat. In time, the reduction in ground temperature will diminish as the BHE and its surroundings approach a state of equilibrium.

7 OPTICAL DEGRADATION OF A BUILDING INTEGRATED UNGLAZED SOLAR COLLECTOR SURFACE

This section presents the study on optical surfaces degradation of the building (roof) integrated flat plate USC (developed in the ENDOHOUSING project, see chapter 5, Fig. 23 (a) and Fig. 24) by exposing USC specimens to a field test consisting of a natural and semi-natural test set-up; as presented in Paper III and IV (Stojanović et al. 2008; Stojanović and Akander, 2008) appended in this thesis. Optical degradation results from USC specimens that have been exposed for ~11 months of natural and semi-natural field testing (at the roof of the Centre for Built Environment Gävle, Sweden; see Fig. 39 and 40), is presented. While the exposure progressed, local and microclimate monitoring was conducted during the field testing, in order to assess and characterize the exposure environment and its degradation agents. The presented data on the microclimate monitoring, displays a longer test period than results from the optical degradation evaluation, as the semi-natural test set-up procedure (in order to increase Time of Wetness) and proficiency evaluation continued for an additional year. The durability issues of solar collectors are in general related a number of problems: erroneous manufacturing, installation or freezing (Wennerholm, 2003). Other durability issues are the exposure to various strains (solar radiation, wind, rain/humidity, snow and airborne pollutants) as a result of outdoor placing and in-service use. This contributes to a degradation process and contamination of the collector material (surface) that affects its energy performance (optical properties). These changes will in turn be transposed throughout the system, lowering its degree of efficiency, which directly relates to the economical and environmental aspects of the system, see Figure 22. As a result of these types of changes, a performance-over-time assessment is needed, so that the progression and effects of the performance lowering degradation processes can be assessed. One of the main questions is, as the ENDOHOUSING USC roof being an active thermal/energy system component (experiencing different temperatures and surface wetness), if it will have an alternate durability and SL in comparison to regular architectural surfaces. As the metallic USC is a regular outdoor surface (not as the absorber coating of a glazed collector), the coating applied on to the component will most likely be of the same type as for regular architectural surfaces (e.g. tin roofs), and having the same durability requirements. These requirements usually do not express optical durability related to the radiation energy transfer parameters: solar absorptance () and IR emittance (), which are vital for solar collector performance (Duffie and Beckman, 2006), nor regard the possibly harsher degradation environment as a result of the USC being an active component. This raises the question if these current coating requirements are adequate for this type of application. Besides the performance impact of the collector surface degradation, there are also aesthetic aspects to the collector degradation, see Figure 38. Especially systems that use dual-purposed roof integrated USC’s, whose purpose is to improve the overall cost effectiveness and blend into their surroundings by not appearing as ‘add on’.

Fig. 38. An example of a tin roof where the surface coating (paint) has been exposed to various strains as a result of its outdoor placing, causing a surface coating degradation and an eventual failure. As previously noted, the USC optical durability tests consisted of a natural and semi-natural field exposure, see Figures 39 and 40. The main idea for the division into these two test procedures is to have a field test set-up which assesses and highlights the extremes of an USC in operation. These being a surface (component) absorbing as much as possible solar radiation, hence experiencing high surface temperatures and UV radiation (this is related to the natural test set-up). The other being that the USC can/will absorb heat from the ambient via convection (see discussion in section 3.1). There will be occasions when air is cooled at the USC surface to the extent that condensation occurs. Roofs also have the tendency for condensation exposure due to night sky radiation (emitting long wave radiation), as they have a large view factor of the sky. These scenarios demonstrate the USC humidity exposure and necessity of durability. 7.1 THE FIELD TEST SET-UP EXPOSURE The natural test set-up consists of USC specimens mounted on to a Plexiglas panel, see Figures 39 (a) and 40. The attachment is realised as holes were drilled through the Plexiglas panel. The USC specimens were placed over these holes, which thereafter were filled with silicone from the backside, thereby attaching the specimens with silicone fillings. This approach enables an easy detachment of test specimens and replacement with an aluminium dummy, in order to preserve the homogenous panel surface. The main purpose of this procedure is the ability to expose entire test panels as apposed to single small specimens (see discussion section 2.2.1). A total of five test panels were mounted onto a rack facing south that is inclined 45, see Figure 40.

(b) Fig. 39. The natural (a) and semi-natural (b) field exposure set-up, of the USC optical durability test; located at the roof of the Centre for Built Environment Gävle, Sweden.

Fig. 40. The natural field exposure set-up of the USC optical durability test. 5 test panels mounted onto a rack facing south and having an inclined of 45; located at the roof of the Centre for Built Environment Gävle, Sweden.

Each test panel holds 16 pre-cut specimens. The necessity of this pre-treating is due to the USC material thickness of 2*10-3 m, which makes it difficult to cut the test samples on site, without damaging or contaminating the specimen and USC surface. The semi-natural exposure was accomplished by mounting USC specimens onto a Direct-Air Peltier-Element (PE), which cools the samples to increase the Time of Wetness (TOW) by reducing the surface temperature, hence highlighting humidity exposure and its accompanying effects, see Figures 39 (b) and 41. The control strategy of the PE was to set a fixed temperature difference between the surface and ambient air, such as to obtain continuous visible surface condensation. As the PE is a Direct-Air type unit, the (directly cooled) aluminium surfaces temperature will follow the outdoor temperature variations with a fixed cooling temperature difference. The set-point temperature is chosen by guidance of monthly outdoor mean-air temperature and humidity. This rough and simple control strategy can in combination with time-to-time visual checkups and adjustments, render a significant overall TOW increase. The convenience of using a PE is the simplicity of only being dependent on electricity. Other set-ups for cooling, usual require some circulating brine or other cooling fluid, in combination with a refrigerator unit.

Fig. 41. Close-up picture of the cooled test surfaces in the semi-natural field exposure testing. A more ingoing USC natural and semi-natural test set-up description can be found in Paper III (Stojanović et al., 2008) and IV (Stojanović and Akander, 2008), appended in this thesis. 7.2 LOCAL AND MICROCLIMATE MONITORING In order to assess and characterize the exposure environment and its degradation agents, local and microclimate monitoring was conducted during the exposure testing. The monitored local meteorological parameters used in the study (at a pre-testing stage (ISO, 2001), see Fig. 2) were: air temperature (C), relative humidity (%), irradiance (global and diffuse solar, and UV (0.295-0.385 m) at a horizontal surface) (W/m2). The microclimate (temperature and TOW) was monitored on the surface of the exposed test specimens with a WETCORR measuring equipment, see Figures 39, 40 and 41. For an extensive description of the WETCORR equipment see Norberg (1998). WETCORR sensors were placed on two separate panels in the

natural field exposure test and one on the semi-natural field exposure test. The mean of the two measured values in the natural field exposure testing is considered to be representative for the microclimate on these test surfaces. As for the semi-natural test, only one sensor is used as a representative measure. Results from the microclimate measurements are presented in Figures 42 and 43.

0 2000 4000 6000 8000 10000 12000 14000

Hours (h)

N 2005-11-01 to 2006-11-01 SN 2005-11-01 to 2006-11-01N 2006-11-02 to 2007-09-12 SN 2006-11-02 to 2007-09-12

0 2000 4000 6000 8000 10000 12000 14000

Hours (h)

N 2005-11-01 to 2007-09-12 SN 2005-11-01 to 2007-09-12

(b) Fig. 42. Cumulative graphs of the measured test surface temperature of the natural (N) and semi-natural (SN) exposure for the test periods (including the prolonged evaluation), see Stojanović and Akander (2008), the appended Paper IV in this thesis.

2005-11-01 to 2006-11-02 2005-11-01 to 2007-09-12

Period

Natural >10 nA Semi-natural >10 nA

Fig. 43. Cumulated measured (estimated) TOW for the natural and semi-natural exposure with the electrical current criteria of >10 nA (from the WETCORR sensor) when the surface temperature is >0 C, for the presented test periods (including the prolonged evaluation), see Stojanović and Akander (2008), the appended Paper IV in this thesis. 7.3 OPTICAL SURFACE DEGRADATION The surface analysis of build-up and compositional changes induced by natural and semi-natural ageing were performed by means of Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDX). The results from the SEM and EDX analysis primarily showed surface pollution (quarts) that predominantly consisted of particles exceeding 10 m in size, see Figures 44.

Fig. 44. SEM picture of a prolific particle (quarts) on a polluted USC surface with x500 magnification after ~6 months of semi-natural field exposure; see Stojanović et al. (2008), the appended Paper III in this thesis.

The quantitative performance characteristic measure of the USC specimens was the optical properties: thermal solar (total and diffuse) and IR (total) reflectance. These parameters were measured by means of spectrophotometry: UV/VIS/NIR and FTIR, on the exposed specimens. In order to transform the measures to the more useful heat transfer parameters of: solar absorptance () and IR emittance (), the measurements were weighted towards the wavelength-dependent direct normal solar spectral irradiance, as recommended by Carlsson et al. (1994) and in accordance to the standard ISO 9845-1 (ISO, 1992), and the radiation emitted by a black body at room temperature (293 K), given by Planck’s law. Results from these measurements are presented in Figures 45, 46 and 47.

2006-09-222006-08-15

2006-04-122005-11-01

2005-10-25 2006-01-03 2006-03-14 2006-05-23 2006-08-01 2006-10-10

Zero N polluted N clean SN polluted SN clean

Fig. 45. Normalised change in total solar absorptance for polluted and cleaned surfaces in the natural (N) and semi-natural (SN) field exposure after ~11 months, see Stojanović et al. (2008), the appended Paper III in this thesis.

2006-09-222006-08-152006-04-122005-11-01

2005-10-25 2006-01-03 2006-03-14 2006-05-23 2006-08-01 2006-10-10

Fig. 46. Normalised change in specular solar reflectance for polluted and cleaned surfaces in the natural (N) and semi-natural (SN) field exposure after ~11 months, see Stojanović et al. (2008), the appended Paper III in this thesis.

2005-11-01 2006-04-12

2006-08-15

2006-09-22

2005-10-25 2006-01-03 2006-03-14 2006-05-23 2006-08-01 2006-10-10

Fig. 47. Normalised change in total IR emittance for polluted and cleaned surfaces in the natural (N) and semi-natural (SN) field exposure after ~11 months, see Stojanović et al. (2008), the appended Paper III in this thesis. The study showed that after ~11 months of natural and semi-natural field exposure did not cause any significant optical (αtot and εtot) or material (coating) degradation (Fig. 45 and 47), although the specular reflectance decreased significantly due to surface pollution (Fig. 46); see also Stojanović et al. (2008), the appended Paper III in this thesis. The semi-natural test set-up showed a considerable increase in USC test surface TOW in comparison to the natural test set-up (~2.3 times longer TOW), due to lower surface temperatures (Fig. 42 and 43); see also Stojanović and Akander (2008), the appended Paper IV in this thesis. This shows that it is possible to achieve a significantly increased moisture exposure, through a relatively simple cooling device (PE) and rough control strategy. The test set-up also proved to be cost effective, as well as convenient for attaining a prolonged surface TOW and highlight humidity exposure, as the PE is only dependent on electricity. Other set-ups for cooling usual require some circulating brine or other cooling fluid in combination with a refrigerator unit. In general, the study presents an approach for field testing and assessing the optical surface durability of active thermal/solar building envelope components, working in a system solution, without having a full system in operation. The results presented in this section and in the study show the first steps in attaining a degradation function of optics. When having such a function and being able to calculate the reduction in these performance parameters, the knowledge can be applied to solar collector energy performance calculations, and finally system simulation to evaluate the affect on the overall system performance, see Figure 22. This chain of events presents the entire course connecting/bridging material degradation to system performance reduction (see also section 2.5). If also having models (in the system evaluation) which can assess their own long-term performance (e.g. the borehole model in Paper II (Stojanović and Akander, 2005)), provides the possibilities for evaluating how and to what extent the components affect each other. An example of this scenario is a system containing a solar collector and borehole. Not only is it possible to evaluate the system performance reduction, but also the dynamic interrelation between solar collector performance reduction in relation to borehole thermal performance. As less solar energy is attained, more energy is extracted from the borehole, hence decreasing the borehole mean-length temperature, in the end resulting in a decreased system performance.

8 THERMAL FLAT PANEL COLLECTOR MODEL This section presents the thermal modelling of the USC flat panel developed within the ENDOHOUSING project (see chapter 5), as presented in Paper VII appended in this thesis, with the aim of producing a detailed yet swift thermal steady-state model. The model is analytical, one-dimensional (1-D) and derived by a fin-theory approach. It represents the thermal performance of an arbitrary duct with applied boundary conditions equal to those of a flat panel collector. Heat transfer simulations and calculations on absorption of heat in flat plate solar collectors, have generally been based on simplified 1-D heat transfer modelling, e.g. see Duffie and Beckman (2006) and Fischer et al. (2004). Traditionally, a fluid element flowing through the collector (or arbitrary duct) is assumed to absorb heat from its ambient in a 1-D manner, along its flow path (Duffie and Beckman, 2006). This approach renders a model that requires small computational resources and time, which is beneficial in system simulations when seasonal or annual performances are analysed. The efficiency and accuracy of the model is adequate for analysing energy performance, calculating bulk or outlet fluid temperatures, or ordinary absorber plate and fluid temperature distributions (Duffie and Beckman, 2006). If detail analysis of temperature fields and heat transfer distributions/variations at steady-state or dynamic conditions are required, more sophisticated and complex models have to be used. For instance, this is needed when solar collectors have a duct/tube fluid volume circumference that is significantly larger (2) than the heat-absorbing surface. In this case regarding the duct/tube as a point in the absorber plate, e.g. see Duffie and Beckman (2006) and Hilmer et al. (1999), is not appropriate. Detailed thermal modelling (of e.g. solar collectors) usually result in a multi dimensional numerical model (e.g. Hassan and Beliveau, 2007). The model can vary in complexity, dependent on the desired level of detail. A detailed numerical model requires a substantial amount of computational power and time, which primarily makes it suitable and useful for specific and detailed case studies; not suitable as a component in system simulations. In some cases there is a need to have a model which can calculate/simulate detailed thermal distributions and variations, without requiring a large amount of pre-processing or computational power and time; thereby attaining a model suitable for component analysis whilst being useful in system simulations. The advantages are that solar collector analysis and optimisation can be performed in junction to system operation at different geographical locations, during long-term simulation scenarios. As an example, this procedure is useful in durability assessments of solar collector absorber surfaces, e.g. see Carlsson et al. (1994). Annual simulations of solar collectors operating in system solutions are performed at different geographical locations, in order to assess the absorber surface microclimatic exposure to relevant degradation agents, such as temperature and humidity (Carlsson et al., 1994; Van der Linden et al., 1990; Holck et al., 2003). In general, durability issues of solar collectors are related to a number of problems: erroneous manufacturing, installation or freezing (Wennerholm, 2003). Other durability issues are the exposure to various strains (solar radiation, temperature, wind, rain/humidity, snow and airborne pollutants) as a result of outdoor placing and in-service use. These contribute to a degradation process and contamination of the collector material (surface) that affects its energy performance due to change in optical properties, e.g. see Carlsson et al. (1994), Stojanović et al. (2008) and chapter 7. These changes will in turn be transposed throughout the system, lowering its degree of efficiency (Hollands et al., 1992), which directly affects economical and environmental

aspects of the system. As a result of these types of changes, a performance-over-time assessment is needed, so that the progression and effects of the performance lowering degradation processes can be assessed. Work on assessing the change in system performance due to solar collector degradation and characterisation of microclimate in/on solar collectors, constitutes one of the most important steps towards SL predictions (Carlsson et al., 1994, Hollands et al., 1992). 8.1 FIN-THEORY BASED USC THERMAL DUCT MODEL A 1-D steady state thermal model based on fin-theory is derived in order to obtain a tool that swiftly calculates the ENDOHOUSING developed flat panel USC’s (see chapter 5) performance: material temperature and heat transfer distribution/variation and fluid temperature. This section presents the model derivation procedure. The basic concept of the 1-D steady state fin-theory is that heat is transported from the fin-base throughout the fin-material in length direction; there is no ‘or negligible’ temperature gradient in the fin perpendicularly to the fin length. While conduction prevails, heat is either emitted or absorbed by the fin depending on the interaction with the ambient (Holman, 2002). The USC flat panel cross-section represented in Figure 48 shows that a thermal symmetry can be applied on a USC flat panel duct, dividing it into a half duct. The USC half duct becomes a system of three fin sheets (Fig. 49). Figure 49 presents the thermal system with applied boundary conditions and defined energy flows used in the fin-theory based model. These boundary conditions represent the thermal course of event in a central duct on flat panel USC. Note; the heat transfer occurring in a centrally placed duct is seen as representing an entire USC panel or roof, see Figure 24 (chapter 5) and 48.

Fig. 48. A cross-section of the ENDOHOUSING flat panel USC. The figure shows the applied thermal symmetry lines on a centrally placed duct that makes a half duct, which is seen as representing the USC thermal behaviour. The model neglects the thermal effects of the two lower feet and the folds at each edge.

Fig. 49. The steady state 1-D heat transfer within a cross-section of the USC half duct fin-theory based model, with applied boundary conditions and defined heat transfer rate directions. 8.2 MATHEMATICAL DERIVATION The following example presents a simplified derivation of the temperature distribution expression of Fin 1, see Figure 50, which is the top fin/sheet of the USC half duct (Fig. 49). For a more ingoing description see Paper VII appended in this thesis.

Fig. 50. The heat balance in a cross-section of Fin 1. The heat balance of over an infinite small element in a cross-section of Fin 1 is according to Figure 49 and 50 as:

)](,[)](,[)](,[)](,[)](,[ 112161541311 zTdxxQzTxQzTxQQzTxQzTxQ fffff

(53) The combination of the above-presented heat flows, in accordance to Eq. 53, will give the partial differential equation:

)](,[)](,[

skyrUSC g,aafff

ThGThzThzTxT

(54) The solution to the partial differential equation (the Fin 1 temperature distribution) in Eq. 54 is:

1121111

)]([)]([)]([)](,[ 1111

ezTCezTCzTxT fxf

xff (55)

The procedure for deriving the fin-temperature distribution for Fin 2 and 3 is in direct analogy with the above presented example. Fin 2 and 3 are applied with the boundary conditions and heat balances that are displayed in Figure 49. In order to be able to calculate the cross-sectional temperature distribution in Fin 1, 2 and 3, the unknown constants in the fin-temperature equations have to be solved. By using boundary conditions as illustrated in Figure 49 and combining the heat transfer rates exiting from one fin and entering another, provides the possibility to solve the unknown constants. The solved unknown constants of the fin temperature distribution equation, in a USC duct cross-section, are defined and presented in Paper VII appended in this thesis. By integrating the heat flux (containing the fin-temperature distribution) over the entire fin length attains the heat transfer rate from a fin cross-section. Eq. 56 presents the heat transfer rate from Fin 1 to the USC fluid (see also Fig. 50).

2311111112

111112111

)()]([)]([

)]([)]([)]([

)]([11

LzTLzTezTC

ezTCzTCzTCh

f (56)

Having derived heat transfer rates from the fin cross-sections to the USC fluid, provides the possibility to calculate the fluid temperature along the USC duct, hence the fin temperature distribution. Eq. 57 presents the steady state fluid temperature along the USC duct. The equation assumes that there is no heat transfer perpendicular to the USC duct cross-section. As the heat transfer rates from the fin cross-sections to the USC fluid contain the variable

)(zT f , the major task is to isolate this term. The procedure used within this work for isolating

)(zT f was to define and redefine, name and rename constants in the heat transfer rates. This

cataloguing procedure requires programming software, e.g. MATLAB. At the end, the equation becomes:

)()(CCe

CCinTzT fpcm

ff −⋅⎟⎟⎠

⎞⎜⎜⎝

⋅⋅

& (57)

By attainment of Eq. 57, the fin temperature distribution at a USC duct cross-section, as well as along the USC duct, can be calculated at steady state conditions. 8.3 CALCULATION RESULTS This section presents an example of calculation results with the fin-theory model, which is also compared (in a simple way) with a steady state 2-D FEM model, of a USC duct cross-section. It has to be noted that as the fin-theory model does not include the heat absorbing/emitting corner surfaces of the top and bottom fins, in comparison to the FEM model (see Fig. 48 and 49 in comparison to Fig. 51 (b)). Thereby the heat fluxes:

)](,[ 13 zTxq f , 4q , )](,[ 15 zTxq f and )](,[ 313 zTxq f are multiplied with the factor

, in order to assess these surfaces in the presented

calculations/simulations. The input data applied to the fin-theory and FEM USC models are presented in the Tables 2, 3 and 4. The climate condition represents a fictive summer scenario: sunny warm ‘Nordic’ weather. The chosen geometrical dimension of the USC duct is equal to the ENDOHOUSING developed flat panel collector, as used in the Swedish demonstration site (see also chapter 5). The USC material is fictively set, in this example, to represent steel. Table. 2. The geometrical dimensions of the modelled USC half duct.

Half duct inner with (m)

Half duct inner height (m)

Top and bottom fin/sheet

thickness (m)

Wall fin/sheet thickness (m)

USC duct length (m)

0.0125 0.013 0.002 0.001 5 Table. 3. Material and fluid data. Note that the USC is coated with an organic paint, hence the applied high α and ε.

Material and fluid λ cp α ε Tf(in)

(ºC) m&

Steel 60 - 0.9 0.9 - -

Water 0.6 4180 - - 5 4.6*10-4

Table. 4. Climate condition.

Gg, USC V Ta (ºC) Tsky (ºC) Tb (ºC)

800 3 20 20 20

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009 0.01 0.011 0.012 0.013 0.0140.01412.9

Fin length x (m)

USC duct, steel, at duct length 1 m

Fin 1Fin 2Fin 3

(b) Fig. 51. Comparison of calculated/simulated cross-sectional fin/sheet temperatures for an exemplifying cross-section at 1 m duct length from Figure 52 and the conditions from Tables 2-4. The comparison is made between the fin-theory (a) and a FEM (b) USC duct model.

Not originally included in the fin-theory model

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 55

USC duct length (m)

USC duct fluid temperature profil

USC duct fluid

Fig. 52. Calculated/simulated USC duct fluid temperature when applying the conditions from Tables 2-4. Results from the calculation comparison presented in this section and the results presented in Paper VII, appended in this thesis, show that the fin-theory model has excellent capabilities of calculating energy performances and detailed material temperature fields and heat transfer distributions/variations (at steady-state conditions); as well as fluid temperature profiles, whilst still being suitable for component analysis in junction to system simulations as the model is analytical. The accuracy of the fin-theory model is high, as long as the fin-theory assumption prevails (no ‘or negligible’ temperature gradient in the fin perpendicularly to the fin length). The derived fin-theory USC model is meant to be used for efficient optimisation and design of the USC flat panels (or similar applications), as well as detailed thermal analysis of temperature fields and heat transfer distributions/variations at steady-state conditions (in junction to system operation at different geographical locations, during long-term simulation scenarios); without requiring a large amount of computational power and time. Detailed surface temperatures are necessary features for durability studies of the surface coating, e.g. reading moisture condensation and TOW, hence the effect of coating degradation on USC and system performance; see the discussion in chapter 7 and Paper III (Stojanović et al., 2008) appended in this thesis.

9 SERVICE LIFE PREDICTION OF DISTRICT HEATING DISTRIBUTION NETWORKS

This section presents the application of the Factor Method (ISO (2000) and ISO (2008) see also section 2.7) on district heating pipes, as presented in Paper VIII appended in this thesis, in order to attain a tool which can be used for SL estimation regarding damage, in this case pipe leakage. Maintenance and repair of construction works is an intermittent process based on two general strategies: reactive (corrective) or proactive (preventive). The proactive strategy may be subdivided in two categories: optimised or non-optimised. Which of these main strategies to apply depends on what function is required of the construction. An optimised proactive strategy requires an all-embracing knowledge about the construction and its life cycle performance behaviour covering: performance requirements, in-use conditions, exposure environment and SL. Whereas, a non-optimised proactive strategy may lead to oversized maintenance, resulting in: inefficient use of resources, reduced economical profit and increased environmental impact. The same consequences may appear if the reactive strategy is applied. Moreover, as the reactive strategy leads to unexpected failures (as actions are taken when failure occurs), the consequences may be serious production breakdowns, neglected safety and customer inconveniences. An optimised proactive maintenance strategy aims to maximise the economical profit, minimise environmental impacts and keep the risk of failure at a low level. Implementation of such strategy in the context of District Heating (DH) requires efforts and abilities for predicting future performances and estimating SL of district heating components. A hypothetical example of the different maintenance strategies and their impact on the maintenance costs is presented in Figure 53. The hypothetical example is based on discussions by Josefsson and Åkesson (1988), Strömwall and Lemmeke (1989) and by personal communications with a DH manager (Hallberg et al., 2007). Note the difficulty in completely avoiding (unexpected) failures, as degradation (which implies failure/damage) has a stochastic appearance, hence uncertainty in failure prediction/assessment (see also discussion in chapter 2). Optimised and proactive strategies will therefore still have a certain share of incorporated reactive elements.

Fig. 53. A hypothetical example of maintenance cost related to: A - reactive strategy, B - non-optimised proactive strategy (increased number of proactive actions) and C - optimised proactive strategy.

9.1 FAILURE CHARACTERISTIC OF DISTRICT HEATING PIPES The two main factors reducing the performance of a DH distribution network are leakage and insufficient/reduced thermal insulation. Leakage is often a performance indicator of DH distribution network (Andersson et al., 1999). Leaky medium pipes (see Fig. 54, mostly steel or copper) leads to fluid, heat losses and reduced system pressure, which in turn may lead to heat distribution breakdowns. Casing pipes (see Fig. 54) may also leak. A leaky casing pipe does not directly affect performance, but may indirectly lead to moisture ingress, which in turn may reduce the thermal insulation and cause medium pipe corrosion.

Fig. 54. Currently the most common DH pipe design (Olsson, 2001). Figure 55 gives an overview of the relation between the two main (on DH pipes) occurring degradation agents/factors, -mechanisms and failures/damages.

Fig. 55. The relation between degradation agents/factors, degradation mechanisms and failure/damage occurring on DH pipes.

9.2 THE APPLICATION OF THE FACTOR METHOD The scope of the study, as presented in Paper VIII (appended in this thesis), concerning SL forecasting (prediction or estimation), was primarily focused on pipe leakage; one of the main and most serious damages occurring on DH networks. Pipe leakage can be seen as an abrupt damage, where there is no performance (fluid transport) reduction until the damage (leakage) occurs. A feasible SL forecasting approach for this type of damage is the Factor Method (ISO, 2000; ISO, 2008); see also section 2.7. The Factor Method is a SL forecasting approach, which estimates the SL (not the degradation/performance over time), by making use of information on a ‘reference’ component situated in a reference in-use condition - with a known reference SL (RSL) - and modifying factors that transform the reference in-use conditions to the condition of the actual case. The Factor Method was, within the study (as presented in Paper VIII appended in this thesis), applied in two specific cases. Case A: to estimate the SL of repaired pipe sections (replacement of pipe) Case B: to estimate the SL of pipes in a new or extended DH distribution network.

The study discussed that the relevant modifying factors which may have significant impact on the degradation/damage occurrence in the two specific cases, are the ones as presented in Table 5. Table. 5. The two cases and corresponding modifying factors.

Modifying factors Case A: Repair of pipe sections

Case B: Installation of new pipe

sections Factor A: Quality of component X (X)

Factor B: Design level X X Factor C: Work execution level X X Factor D: Indoor environment

Factor E: Outdoor environment X Factor F: In-use condition (X)

Factor G: Maintenance level In case A, i.e. when to estimate the SL of a repaired DH pipe section (the replacement pipe), it is assumed that the prevailing set of conditions that have caused leakage on the DH pipe section will constitute as reference condition. The SL of the damaged pipe section will consequently constitute as RSLC. The DH network in question can therefore be seen as a single big ‘living’ RSLC database. However, there is some additional reference information that is not provided by the ‘living’ RSLC database. This type of ‘additional’ reference information refers in case A to the quality of workmanship (factor C), which in turn can be correlated to the construction intensity at the time of installation of the replaced (damaged) pipe. Information on the construction intensity and responsible contractors is likely to be found in databases or archives at the DH suppliers. The application of the Factor Method in the design phase of new or extended DH distribution networks (case B) differs from case A, as all of the RSLC data has to be gathered from a predefined RSLC database. The modifying factors, which are concluded to have decisive impact on the SL estimations, correspond primarily (in this case) to factors B, C and E, and

to some extent also factors A and F (Table 5). Given that the set of reference in-use conditions are similar to the condition of the specific case of interest with respect to pipe quality and design, then factor A can be ignored (or set to A = 1). If not, i.e. if the reference data is based on ‘old’ pipes where the pipe design and quality significantly differs form pipe design and design codes commonly applied ‘today’, it should be considered whether or not the RSLC data is appropriate/acceptable for its intended use at all. The application of factor F refers in this study to mechanical impact due to operational conditions such as fluid temperature and pressure variations. It is assumed that the reference operation conditions of the specific case, due to temperature and pressure variations, are similar to the reference in-use conditions. However, future change of operational conditions should be considered, as such change may affect the degradation/damage process. It is always up to the user to set or find the modifying factor values. The factor values, which theoretically may have a value between 0 and infinity, should preferably be close to the reference in-use conditions, i.e. value 1 (ISO, 2008), but may in some cases be determined based on the users/evaluators own experience and knowledge. In those cases, the factor method can be regarded as a refined checklist (ISO, 2008). Alternatively the user may find appropriate data enabling the user him/herself to calculate the factor values or find tabulated factor values (e.g. Hovde, 2005) generated by ‘experts’, which are based on statistical data derived from a RSLC database or similar. Applying degradation models would be an alternative approach to determine the values of e.g. factor E (in case B), since the long-term influence of the exposure environment cannot be (or is unlikely) measured in real time. Applying this approach requires a profound knowledge about the time dependent degradation process and utilisation of mathematical models describing this process. This approach can be complex as the degradation process leading to damage may consist of a number of sub processes.

10 SUMMARY OF RESULTS WITHIN THE STUDIES The specific studies (the appended papers) were predominantly performed in association to the EU project ENDOHOUSING. The project constituted the platform for the work on lifetime performance of thermal systems, hence outlining the main context of this thesis and the studies presented within on: Flat plate solar collectors.

- A literature review on degradation; field exposure (regarding optical surface degradation) and adapted thermal modelling of the ENDOHOUSING developed roof integrated USC.

A literature review on the degradation of optical characteristics of glazed solar collectors; Paper I. This literature review, specifically the IEA Task X study (Carlsson et al., 1994), was the starting point for a similar investigation on coated metallic USC (as presented in Paper III and IV). The knowledge and results from the IEA Task X study (as presented in Paper I) makes up an innovative and comprehensive durability assessment procedure. The established accelerated selective absorber coating degradation testing and modelling, ties material degradation to optical measures vital for solar collector performances. Furthermore, the performance criteria applied on material degradation is set in relation to altered system performance, thereby attaining a criterion which bridges material to system performance. The Task X study provides a vital base knowledge on how to perceive durability and lifetime performance of thermal systems. The Task X study has been an inspiration for this thesis and the work performed within. Optical surface degradation assessment of the ENDOHOUSING developed USC, through field exposure testing; Paper III and IV. Inspired by the Task X study (Paper I), the overall aim was to establish a field exposure test set-up (in order to test the optical surface degradation of the USC) by developing a natural and semi-natural filed exposure, which highlights the extremes of a USC in operation, without running a full system. One of the main questions is, as the roof-integrated USC being an active thermal system component (experiencing different temperatures and surface wetness), if it will have a different durability and SL in comparison to regular architectural surfaces. Field exposure tests where performed at a pre-testing stage, in line with the ISO 15686-2 standard (ISO, 2001). Though this study was not completed all the way, an outlined methodology and preliminary test results are presented in Paper III and IV. In order to highlight USC humidity exposure and its accompanying effects (semi-natural filed exposure), USC samples were mounted onto a Peltier-Element (PE). The PE cooled the samples in order to increase TOW, hence simulating active cooling (USC in operation). The PE proved to be proficient, inexpensive and flexible for this purpose, see Paper IV. The results from the study show the first steps in attaining a degradation function of optics. In general, the study presents an approach for field testing and assessing the optical surface durability of active thermal/solar building envelope components, working in a system solution. Adapted thermal modelling of the USC; Paper VII. A steady state thermal model was developed, for future analysis of the short and long-term thermal performance of the USC flat panel. The model is meant to be used for efficient optimisation and design of the USC flat panels (or similar applications), as well as detailed thermal analysis of temperature fields and heat transfer distributions/variations at steady-state conditions (in junction to

system operation at different geographical locations, during long-term simulation scenarios); without requiring a large amount of computational power and time. Detailed surface temperatures are necessary features for durability studies of surface coatings, e.g. reading moisture condensation and TOW, hence the effect of coating degradation on USC and system performance (Paper III). The goal is to link the results from the USC-experiments (optical degradation as presented in Paper III) into this model, thereby creating a USC performance-over-time model. Ground heat sources/storages and interaction with a heat pump system.

- Performance evaluation of the compact ground heat exchanger, acting as seasonal heat storage at the Swedish Endosite; adapted long-term thermal performance modelling of a borehole and its effect on a heat pump system.

The performance of the compact Ground Heat Exchanger (GHE), used in the Swedish Endosystem (SAHPS) as a heat storage and source (Paper IX), indicates that the present ground heat storage design e.g. concerning: ground depth, soil type, surface area and GHE configuration, is not capable of extensive seasonal heat storage. However, the intermittent operation of the Swedish Endosystem, during spring and autumn, enables thermal recharging of the heat storage, hence sufficient system operation and heat delivering. In order to make an extensive analysis of improved thermal storage capacity, a relevant model of the GHE and its surroundings has to be developed. At present time, such a model is not readily available. Within the ENDOHOUSING context, a computational borehole exchanger model was developed to explore the influence of long-term heat extraction from the ground. The novelty was the development of a model that is a relatively simple RC-network which can be used for swift simulations (Paper II). In order to highlight how the degradation of a component in a system (the successively cooled BHE) influences the thermal performance of the entire system, the BHE model (as mentioned previously) was ‘attached’ to a additionally derived model representing a HP system and building with a heating requirement (Paper V and VI). As shown in the study of Paper V, there is no significant HP system performance reduction, due to borehole temperature decrease, after about 10 years operation in this particular example. This exemplifies the performance-over-time assessment of a thermal system and the usefulness of having engineering tools (in this particular context). Evaluation of the ENDOHOUSING developed solar-assisted heat pump system.

- Long-term system performance evaluation of the Swedish Endosite SAHPS. Concerning the Swedish ENDOHOUSING SAHPS; analysis showed that despite unfavourable building conditions, for low energy use and utilisation of a SAHPS, the system was successfully in full operation (for about two years) fulfilling heating requirements; Paper IX. Data processing presented a HP and total SAHPS performance of: SPFHP=2.85 and SPFSAHPS=2.09. It is argue that with an optimised SAHPS control and operation strategy, additional use of primarily circulation pumps could be vastly reduced, hence attaining a SPFSAHPS value that is equivalent to the SPFHP. As the Nordic (Swedish) ENDOHOUSING SAHPS has not yet been properly optimised/designed and installed in a ‘appropriate’ house, the SPFHP=2.85 is considered as being a success.

The only non ENDOHOUSING associated work, presented in this thesis, is the study of SL prediction and estimation of DH distribution networks (an additional thermal system application) through the implementation of the Factor Method.

The implementation of an optimised and proactive maintenance strategy, in the context of DH, requires efforts and abilities for predicting future performances and estimating SL of DH components. Durability and SL assessment can be complex. An example is District Heating networks. A major problem is that the pipes are located in the ground, thereby preventing inspections and the attainment of time dependent information on exposure (degradation) environment and component condition. Paper VIII is composed of two parts: a literature review that assesses the most common problems/damages encountered in Swedish DH networks (pipes). The second part discusses how a SL forecasting method (based on the Factor Method) can be adapted for this application. The literature review on failures (damages and performance reductions) occurring on DH pipes, reveals that failures in DH pipes are mainly consisting of leaks due to corrosion or mechanical impacts and reduced thermal insulation performance. A feasible SL estimation method for DH pipe leakage, as discussed in Paper VIII, is the Factor Method (ISO, 2000; ISO, 2008). The appropriateness of the Factor Method is the possibility to assess and incorporate a variety of factors affecting the SL, although the main and strenuous task is to attain the required information in order to apply the method. Paper VIII focuses on describing the method and discusses the possibilities on how to apply it in two specific cases with respect to leakage: SL estimation of repaired DH pipe sections (i.e. maintenance of DH networks) and of DH pipes in new or extended DH networks.

11 DISCUSSION AND CONCLUSIONS The main questions today concerning thermal systems are their economical and environmental impacts. These entities are generally, at present, assessed on the basis of operation performances of newly installed/designed systems, during an assumed lifetime period. While this is the common way of perceiving thermal systems, performance-over-time will change as an effect of degradation, and not solely of different operation scenarios. How and to what extent is the question that needs assessing in order to evaluate if these changes will jeopardise the intended system performance requirement, hence service life (SL). The lack of knowledge/approaches and tools for assessing durability and performance-over-time of thermal systems complicates the task of incorporating these aspects in engineering. The durability of materials, components and systems is not a topic that is an end in itself, but becomes a vital part in a comprehensive perspective as sustainability. The lifetime performance assessment of thermal systems, as presented in this thesis, shows that it is a vital part of the R&D in the quest of sustainable energy/thermal systems and energy use. Directives (CPD and EPBD), laws (the Swedish law of energy declaration of buildings) and regulations (BBR) of today, clearly express claims of performance-based requirements of construction works, of which the working life is an essential part. These also lay emphasis on construction works to fulfil the set requirements not on the basis of individual parts, but as an assembled system. Currently, the main obstacle for durability and performance-over-time assessment of thermal systems is the lack of knowledge/approaches and tools. An overview of R&D projects and published papers/reports in this field of research shows that the extent of research and knowledge is sparse; pointing out that further R&D is needed. The bridging of material/component degradation (in relation to some thermal performance characteristics) to system performance can be obtained through system stimulations. Vital for these types of simulations is the attainment of adequate material/component degradation and performance models. In this context, it is necessary that the material/component performance models are detailed and accurate, yet not requiring a large amount of pre-processing or computational power and time; thereby being suitable for component analysis whilst being useful in system simulations. Regarding the requirement on model detail and accuracy, it is necessary in order to adequately assess the exposure of degradation agents on a micro level, e.g. temperature and moisture; hence the transformation of the exposure (degradation) environment from a higher geographical scale (e.g. macro or local, see section 2.1). The bridging of degradation (material/component) to component performance (thermal) can be made through the obtainment/use of degradation models (of some particular material or component, in relation to some thermal performance characteristics), e.g. dose-response functions. As the performance models should not require a large amount of pre-processing or computational power and time, the performance-over-time analysis can conveniently be performed (in junction to system operation) at different geographical locations, during long-term simulation scenarios. Although it has to be stressed, that it is vital that the degradation model (e.g. dose-response function) is valid for the different geographical location assessments, regarding degradation agents and mechanisms (see section 2.4). Additionally, it has to be noted that the occurrence of chain reactions can complicate the task of performing a ‘real’ system performance-over-time scenario assessment (simulation). As a

specific material/component degrades, its individual performance reduction may not only singularly affect the system performance, but also the durability of other materials/components in the assembled system; hence multiple material/component degradations are synergistically affecting the system performance. If the system or component performance-over-time (based on material degradation) assessment is not viable, due to lack of knowledge on material/component degradation or complex chain reactions, information on damage and SL (given that a performance requirement is defined and set) may be obtained from statistical surveys. This approach does generally (depending on the scope of the survey) not render a performance-over-time function as it attempts to statistically estimate a lifetime period; nor is the damage and SL correlated to the service/exposure (degradation) environment, it represents the conditions from where the survey was performed. As for the studies within this thesis, the thermal modelling of the borehole, heat pump system and USC, exemplifies the development and attainment of adapted models, aimed for durability and lifetime performance assessments of a thermal system, and the usefulness of having engineering tools (in this particular context), as previously discussed. The work on the borehole and heat pump system modelling and performance-over-time simulations, presents the complete assessment of component degradation and the transformation/bridging to system performance-over-time. This particular study/work was exceptionally suitable for adapted thermal modelling and the bridging/transformation of component degradation to system performance, as the only parameter affecting the performance-over-time was the borehole temperature. The study on the exposure test set-up and analysis procedure of USC specimens, presents an approach for field testing and assessing the optical surface durability of active thermal/solar building envelope components, working in a system solution, without having a full system in operation. The study shows the first steps in attaining a degradation function of optics. When having such a function and being able to calculate the reduction in performance parameters, the knowledge can be applied to solar collector thermal performance calculations and finally system simulations, to evaluate the affect on the overall system performance. This chain of events presents the entire course connecting/bridging material degradation to system performance reduction. If also having models (in the system evaluation/simulation) which can assess their own long-term performance (e.g. the borehole model as presented in this thesis), provides the possibilities for evaluating how and to what extent these components affect each other. In conclusion to the work done within the context of flat plate solar collectors; it shows that the coupling of thermal computational models can be linked with data used for degradation assessments. However, the optical characteristics (and contamination), in this case, have to be assessed through empirical studies (e.g. measurements) and the procedures/methodologies as listed in chapter 2. Another challenge is that the thermal model may not be suitable for this purpose: the level of detail may be wrong, and important parameters (degradation agents) may be missing. The level of detail is also important in terms of computational resources and time – durability simulation studies usually require simulations of long time periods at different geographical locations. One more aspect is important: building-integrated energy components are active – these will obtain other microclimates than ordinary building components. It is therefore necessary to stress that durability data that is applicable to ordinary components may not directly applicable to actively heated/cooled components. Regarding the study on SL prediction and estimation of DH distribution networks; the implementation of an optimised and proactive maintenance strategy, in the context of district

heating, requires efforts and abilities for predicting future performances and estimating SL of district heating components. A feasible SL estimation method for district heating pipes, in view of pipe leakage, is the Factor Method. This study exemplifies the performance of a thermal system, regarding pipe leakages, which basically has a performance condition state: damage or no damage; hence making the use of the Factor Method adequate, as it only means to estimate the SL and not the performance-over-time. Furthermore, the usefulness of the method is also due to the possibility to incorporating additional/multiple factors affecting the SL. Since the district heating pipes are located in the ground, inspections and the attainment of accessible time dependent information on exposure (degradation) environment and component condition is limited; thus the occurrence of damage or SL have, for now, to be estimated by means of statistical surveys. As for the long-term performance evaluation of the Swedish ENDOHOUSING SAHPS; the full performance potential of the system has still not been evaluated, primarily as the GHE (heat storage/source) has not been optimised and evaluated in detail, due to the lack of a (readily available) proper thermal model. By having such a model, the future system performance evaluation and optimisation can be preformed by simulations. Although the system evaluation was performed during a number of unfavourable conditions (see chapter 5), the system performance and operation are seen as successful. Vital findings, which are in line with previous studies (Kjellsson, 2004), is that the use of energy (electricity) for supporting components, such as additional circulation pumps, must be at a low in order to obtain a high system performance. The questioned that needs further evaluation is: what is the full potential of the system when properly optimised, installed and operated, regarding: performance, cost and practical use. Conclusively; this thesis gives knowledge to the thermal (energy) system/technology R&D and engineering sector, regarding durability and lifetime performance assessment methodologies; but also to the durability of construction works sector, regarding the needs for assessing lifetime performance of materials and components in relation to system performance. It also presents descriptions of requirements on construction works. Specifically, the studies presented in the thesis show how durability and lifetime performance assessment of thermal systems may be sought-after, with knowledge on: methodologies, exposure test set-ups, modelling and the attainment and use of adequate tools. The main findings, within the context of lifetime performance assessment of thermal systems, is that major advances in degradation, performance-over-time and SL forecasting methods can be achieved through adequate modelling (see Fig. 56), enabling: simulation and transformation of degradation agents from higher to lower

geographical scales the bridging of material degradation to component performance simulation and transformation of material/component to system performance

degradation the assessment of the above at different geographical locations, during long-term

simulation scenarios in junction to system operation Vital for the overall SL analysis is that the effect of material/component degradation has to be related to system performance. The main issue on lifetime performance of thermal systems is how and to what extent performance reduction in individual materials and components influences the overall system performance, as the essence of thermal/energy system sustainability lays in system performance.

Fig. 56. A graphical exemplification representing the bridging/tying of thermal/energy performance with material degradation, through adapted heat and mass transfer modelling. Thereby attaining performance-over-time assessment models/tools, to be used in order to incorporate these aspects when engineering thermal systems; hence enabling the forecasting of SL.

Material degradation/performance

Thermal/Energy performance

Empirical and semi-empirical degradation

models

Physical and semi-empirical thermo-, fluid-dynamic and

heat transfer models

Performance-over-time models

(adapted heat and mass transfer modelling)

12 FUTURE WORK A solitary report, work or thesis is seldom as comprehensive that all aspects of its particular area has been analysed, assessed and accounted. This thesis is no exception. This thesis gives knowledge to the thermal (energy) system/technology R&D and engineering sector, regarding durability and lifetime performance assessment methodologies; but also to the durability of construction works sector, regarding the needs for assessing lifetime performance of materials and components in relation to system performance. It also presents descriptions of requirements on construction works. Specifically, the studies presented in the thesis show how durability and lifetime performance assessment of thermal systems may be sought-after, with knowledge on: methodologies, exposure test set-ups, modelling and the attainment and use of adequate tools. The R&D area of lifetime performance assessment of thermal systems and (in general) durability of construction works has a variety of continuing R&D to be made, some of which is specifically recommended: Further development and attainment of material and component degradation models,

which are related to the service/exposure (degradation) environment. Far from all materials/components, locations/regions and types of degradations have available semi-empirical or dose-response (empirical) degradation models/functions. Degradation models are key elements in order to perform lifetime performance assessments.

Further work on developing and attaining degradation and performance-over-time

assessment exposure test set-ups, models and tools of thermal systems, which tie material/component degradation (hence exposure environment and in-service use) to altered thermal performance, to be used in order to incorporate these aspects in engineering.

Continued R&D work on the use of the Factor Method for SL forecasting of DH

distribution networks, regarding DH pipe leakage, in order to obtain an optimised proactive maintenance strategy.

Regarding the Swedish ENDOHOUSING SAHPS. The development of an appropriate

model of the GHE and its surroundings, in order to simulate/evaluate its and the Swedish Endosite SAHPS full performance potential. At present time, such a model is not readily available. As the GHE is located in soil, the thermal storage process is not only described by ordinary heat transfer, but is also significantly dependent of moisture transport (from precipitation, water tables, surrounding soil, snow layers, etc. affecting thermal parameters) and phase change (vapour/water/ice). The effects of moisture will make the GHE model complex and at the same time it has to be suitable in system simulations, hence restricted amount of computational power and time.

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