effects of skylights refurbishment on the indoor hygrothermal environment of a gallery space in a...

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Proceedings of the Global Conference on Energy and Sustainable Development GCESD2015

February 24-26, 2015, Technology Park, Coventry University Coventry, UK

GCESD4015

EFFECTS OF SKYLIGHTS REFURBISHMENT ON THE INDOOR HYGROTHERMAL ENVIRONMENT OF A GALLERY SPACE IN A HISTORICAL BUILDING OF

CULTURAL SIGNIFICANCE

Fan Wang*, Yinqi Zhang, Shashwat Ganguly

Royal Academy of Engineering Centre of Excellence

in Sustainable Development Building Design

Heriot-Watt University

Michael Browne

Operations Department

National Galleries of Scotland

ABSTRACT

This paper reports a systematic study on an assessment of the

effects of skylights refurbishment on the indoor hygrothermal

environment of a gallery space in a national gallery building

housed in a historical building of architectural significance. A

CFD model was developed and validated by two sets of

measured data: one collected before the refurbishment and

the other after. The model was used to simulate six

representative scenarios of normal operation of the gallery for

both before and after the refurbishment. In parallel, a

quantitative assessment was developed to analysis the

modelling data and assess the impacts of the refurbishment

and quality of the indoor hygrothermal conditions. The

modeling results were plotted to show the daily fluctuation

and vertical gradient for the key environmental variables

before and after the refurbishment. This would allow designers

and gallery curators to determine the suitable height for

displaying the humidity sensitive paintings according to the

quality of skylights and the degree of tightness of

hygrothermal control. As a part of a three-year project of

renovation of the gallery building, this work is expected to

produce some guidance for developing renovation solutions

for historical buildings as a part of the campaign of carbon

reduction and building conservation and quantitative methods

for post-refurbishment assessment.

Keywords: hygrothermal control, modelling, CFD, assessment,

daily fluctuation, spatial gradient, refurbishment, skylights

INTRODUCTION

Built in mid-19th century, The National Gallery Scotland is a

stone-built classical building. The external walls are made of

sandstone over 1 meter thick and with no fenestration leading

to the display spaces and the roof structures are un-insulated.

A large skylight at roof level provides the natural lighting for

one of the display space and the skylights were single-glazed,

poor-quality work of the 1960s.

Skylights play a crucial role in galleries, museums and libraries,

as they provide natural lighting to the interior spaces of these

buildings. But on the thermal side, they present some

problems due to their high U-values, such as excessive heat

loses, low surface temperature that increases risk of

condensation. Among them, the most problematic one is the

diurnal fluctuation of the indoor air temperature and relative

humidity, especially to gallery spaces that require stable

hygrothermal condition for conservation purpose of the

artefacts on display. This increases both the risk of damage to

the artefacts and the energy consumed by the Heating

Ventilation Air Conditioning (HVAC) system when a tight

control is applied.

A refurbishment, including replacing the skylights with

high performance glazing panels and adaptable control band,

was carried out to reduce the excessive energy bill and

improve thermal performance(Wang et al 2013).

Aim & Objectives

The aim of this study is to assess the effects of the skylight

refurbishment on the quality of the hygrothermal condition in

one of the typical gallery space and energy consumption.

METHDOLOGY

To achieve the aim, the following objectives were made:

*correspondent author: [email protected]


1) To conduct a monitoring measurement to collect data

before and after the refurbishment for validation of a CFD

model for a modeling study.

2) To develop a CFD model to carry out detailed comparison

of before and after the refurbishment under a number of

typical operation conditions

3) To design typical cases and validate the model to ensure its

robustness

4) To design operation scenarios for comparison

5) To develop an assessment criteria with identified variables

for the simulation result

6) To compare the result of before/after refurbishment using

the assessment criteria

7) To conclude the impacts of the skylight refurbishment on

the indoor hygrothermal conditions of a gallery space

Monitoring measurement

Due to the scale of the project, only one space, Gallery 11 was

examined. This was also because there was some

refurbishment, which was carried out in stages to allow the

most parts of the gallery remaining open to public

Fig 1, The ground-floor plan & cross section of the gallery

space examined (1-4 T sensors; 1 RH sensor & 5 Ryranometer).

As the space was an operational gallery, only small thermal

couple sensors were used and humidity sensors were too

visible to be used in this display space and therefore the

humidity was only measured at the visitors’ level by a sensor

behind a statue. The measurement was conducted in two

period time, one before the refurbishment (01/04 – 30/06,

2012) and after (05/04 – 31/07 2014).

Also used were the data extracted from the Building

Management System (BMS) for the specific periods before and

after the refurbishment.

CFD model

CFD has been widely used as an effective tool for studies of

airflow and heat transfer in HVAC for its speed in modelling

and capability in revealing airflow details (Gharpure 2014). This

becomes more attractive when real monitoring is restricted in

either an operating space or a historical building with high

restriction(D’Agostino et al 2013). But before simulation starts

a series tests need to be taken, including a systematic

verification and validation(Eca & Hoeskstra 2014).

The CFD model developed in this study take Gallery 11 (Fig 1).

Like other 12 display spaces, it had an octagon plan and a

smaller copular with a skylight on the top, 9 meters above the

floor (Fig 1). The total volume of the space was 772m3 There

were one air supply at 5.25m above ground floor on the west

wall and two extracts at floor level on to the Northeast whilst

the other, the Southeast.

a) The geometry

b) Arrangement of the lights (left) and occupants

Fig 2 The CFD model

1

4

3

5

2


There are two large openings linking the neighboring galleries

which were maintained at the same conditions, hence the

disturbance from these two neighbours was ignored.

Heat loads calculation & boundary conditions

The loads calculation to specify the model was based on CIBSE

Guide A (2006).

The casual gains include lighting and occupants. The lighting

heat gains, both before and after the refurbishment, were

obtained from the Estate Management Team in the Gallery

(Table 1). The value after refurbishment was significantly

reduced, as one of the measures in the refurbishment is to

reduce energy consumption. The occupant numbers, before

and after were about the same, hence one figure was used for

modeling and it was derived from the weekly counts and

assumption of one hour stay for each visitor. More details can

be found in Zhang (2014)

Validation

Selected for the model validation were four cases. Each one

was characterized with large diurnal changes in the

temperature, relative humidity and solar radiations, all of

which contributed to large change in the loads of the gallery

space during one day cause, and consequently, required

heating, cooling, humidifying and dehumidifying. The first two

cases were on cold date, 1st

of April 2012, morning and

afternoon and the third was on 1st

June afternoon, 2012,

where there was a strong solar penetration. The forth one was

on the 13th

of May 21st

June, also with high solar radiation.

Such selection allowed the model to be set to a widest range

of variables for the testing.

Table 1: Four designed cases for validation and their input (#1

NGS; #2 CIBSE calculation; #3 BMS; #4 BMS+calculation)

Case 1 Case 2 Case 3 Case 4

Heat gains (kW) & ventilation

01/04/12 07:00

01/04/12 16:00

01/06/12 16:00

13/05/14 16:00

light (W/lamp) #1 0 23.05 23.05 4.61 Occupants (W/person) #1 0 75 75 75

Occupants vapor(g/s) #1 0 0.05 0.08 0.05

Skylight gains (kW) #2 -2.72 -0.58 0.24 -0.19

Roof gains (kW) #2 -1.61 -0.34 0.14 -0.28

Infiltration (kW) #2 -3.11 -1.12 -0.75 -1.00

Solar penetration (kW) #2 1.21 3.06 4.59 3.33

Outdoor air T (°C) #4 2.8 15.52 17.74 16.33

Room control T (°C) #3 21.66 22.29 22.28 22.4

Room control RH (%) #3 45-60 45-60 58 47

Supply air T (°C) #4 28.05 20.3 19.6 20.8

Supply air RH (%) #4 35 41 61 51

Supply flow rate (kg/s) #4 0.96 1.08 1.97 1.86

Designing the scenarios & assessment criterion

To assess the effects of skylights replacement, six scenarios

were designed to compare before and after the replacement

(Table 2 is a summary and Appendix for details). Each of the

scenarios was simulated by the CFD model and results are

arranged in pairs to show the difference before and after the

refurbishment, for example: results of BWA and AWA are

plotted into one chart to show a winter AM before and after

the skylights replacement.

Table 2: 12 scenarios designed and simulated for comparison Before refurbishment After refurbishment

winter mild summer winter mild summer

am pm am pm am pm am pm Am pm am pm

scenarios BWA BWP BMA BMP BSA BSP AWA AWP AMA AMP ASA ASP

The management team in the gallery were aware that the

indoor environment control was tight for the gallery space,

maintained at 16~19 ± 1°C for air temperature and 45 ~ 60 ±

5% for relative humidity (BS 5454) and regarded this as the

major causes for high services cost. An adaptable control was

suggested (Harley Haddow, 2012) and examined using

computer modelling (Wang et al, 2013). Based on these

studies, control of three bands – for winter, mild seasons and

summer time was applied in this study (Table 3).

Table 3: Adaptable control bands Period T, °C RH, %

Dec – Feb 18.5-21 41-55

Mar-May & Sept – Nov 19-22 45-60

Jun- Aug 19.5-22.5 47-63

The predicted results were arranged to show the daily

fluctuation and vertical spatial gradient for the air temperature

and relative humidity to assess the indoor hygrothermal

stability and uniformity, the two extra aspects that are

suggested by art conservationists (Camuffo 2014).

Furthermore, the assessment was made by comparing the

heat loses through skylight before and after the refurbishment.

A more detailed comparison is reported in a parallel study

(Sheng, 2014)

RESULTS AND DISCUSSIONS

Verification and validation

The final model had 573,852 cells, which is equivalent of 740

cells per m3 of the flow domain and all cases took around 4

hours to complete 1000 iterations to reach convergence on a

PC with a Core™ i7-4710MQ Processor.

All cases show good agreement between the measured and

modelled for both the temperature over 4 heights and relative

humidity (Fig 4). Although the CFD model appears

underestimated the spatial temperature gradient in the space

and relative deviation, ΔT/T is always less than 15%. The


highest happened close to the top, which far above display

space. The ΔRH/RH is even smaller, less than 10% (Fig 5).

a) Early morning on the cold day in 2012

b) Later afternoon on the cold day in 2012

c) Later afternoon on the warm day in 2012

d) Later afternoon on the warm day in 2014

Fig 3. The measured and modelled (left) and the relative

difference (right) of the four selected cases for model validation

Figure 5. Comparison of RT for all four cases

Indoor hygrothermal conditions

Charts in Fig 6 plots the two key indoor environmental

variables together to show their stability and vertical gradient

before and after the refurbishment. The daily stability is shown

by the distance between the solid (early morning) and the

dashed lines (afternoon) in black for before the refurbishment

and in white for the after. Each of these lines shows the

variable varies with the height: a straight line means no

gradient and even distribution whilst a bent part means the

unevenness.

On the cold day, the black lines (before) show that the AM and

PM fluctuations is significantly larger that the white ones

(after).

a) Cold day


b) Mild season

c) Summer day

Fig 6. Comparison of the fluctuation and vertical spatial

gradient for the two environmental variables for the six

scenarios before and after the refurbishment.

If we focus on one line, the black varies larger than the white

from top to bottom, showing the unevenness (Fig 6a). These

vertical gradients were larger in mild seasons and reached the

peak in summer (Fig 6c). This was due to the air underneath

the single glazing which was influenced greatly by the outdoor

conditions.

The vertical gradient for the white lines are always smaller

than that of black ones. And the changes from the dashed to

solid of the white (after) for three weather conditions are

much smaller than those for black ones. All these indicate a

much better indoor environment was achieved after the

refurbishment.

Relative humidity distribution and daily fluctuation

The relative humidity is the critical environmental variable for

galleries and museums. The CFD model was able to reveal

detailed distribution over the space. Figure 7 shows the daily

change of the RH over the Gallery 11 over three typical

seasons. Plots a)s and b)s represent before the refurbishment

whilst c)s and d)s; the after.

Obviously, larger relative humidity changes were observed in

the occupied zones before the refurbishment than that

observed after. Since the temperature near the surfaces of

single glazing was very low, the relative humidity rose. The

layer of red zone at the top indicates a high risk of

condensation damage (Fig 7a & 7b). Fortunately, this

disappeared after the refurbishment and the zone is yellowish

green, around 50-52% over almost all the room space (Fig 7c &

7d).

Fig 7a-7d The Relative humidity distribution in the morning

and afternoon for both before and after the refurbishment on

a winter day. Fig 7e and 8f reveal a big change in the relative

humidity from morning to afternoon, before the

refurbishment. There is not such change between Fig 7g & 7h,

representing the period after refurbishment, which means the

reduction on the fluctuation of this variable. This is a

confirmation on the improvement on indoor environment.

It should be mentioned that both the Fig 6 and Fig 7a-7d show

an obvious vertical gradient from top (9 m) to the visitor level.

But the lower part had been rather even. This is believed

because of the air supply, its position, height and volume were

all properly designed to ensure a good flow mixing with the

gallery space. The exception was those in the early morning

during mild seasons, when there was a reversed straitification

resulting in low RH (47%) at the visitors’ level and high RH

(52%) at 5 m height (Fig 6b & Fig 7a).


Cold Mild seasons summer

a) BWA: Early morning 2012 e) BMA: Early morning 2012 i) BSA: early morning 2012

b) BWP: Afternoon 2012 f) BMP: Afternoon 2012 j) BSP Afternoon 2012

c) AWA Early morning 2014 g) AWA Early morning 2014 k) ASA Early morning 2014

d) AWP Afternoon 2014 h) AWP Afternoon 2014 l) ASP Afternoon 2014

Fig 9 RH distribution in the early morning and afternoon for both before and after the refurbishment on the three periods of time


Environmental control

In Fig 8 the boxes represent control bands for the three

weather conditions. The charts show that on two occasions,

the indoor condition went beyond the control band, one in the

afternoon mild season and the other early summer morning.

But after refurbishment, all indoor conditions fall into of the

control bands.

a) The temperature in morning and afternoon

b) The relative humidity in morning & Afternoon

Fig 8 the indoor hygrothermal variables against control band

over three typical days during a year.

Heat losses through skylights

As expected this part shows clear improvement after the

replacement (Fig 9). The reduction was not just due to

decrease of the U-value of the skylights, which dropped more

than 60%, but also to the variable control conditions to reflect

the seasonal changes outdoors. Both sensible and latent loads

were reduced.

A close look reveals that most saving was made in cold

weather, either in the winter days or morning during the mild

seasons (the three ovals), where there was a need for both

sensible heating and humidification. The reduction rates are

between 70 – 93 %. In summer afternoon, the cooling and

dehumidification were also reduced (more than 50%

reduction).

Fig 9. Comparison of the heat losses through the skylights

before and after the replacement

CONCLUSIONS

The CFD model was robust and model results were reliable,

based on which the predictions of the 12 scenarios were also

validate.

The indoor environment was improved after the

refurbishment, in terms of daily fluctuation and vertical spatial

gradient of the two key environmental variables, air

temperature and relative humidity.

Over all the refurbishment reduces the daily fluctuation for

both the temperature and relative humidity and smooth the

vertical distribution for both the two variables. The low part of

space, 5m above the floor, had been rather even all the time.

Before the refurbishment, the evenness was not good in the

mornings of mild seasons.

Before the refurbishment, there was one scenario, when the

relative humidity went out the control zone and extra

humidification was needed, and other, when the temperature

was too low and extra heating was required.

To sum up the refurbishment, especially the skylight

replacement made a significant contribution towards energy

saving, primarily for cold weathers through heating and

humidification. Summer saving was also noticeable.

ACKNOWLEDGMENTS

The authors would like to thank Liam Nisbet, the Facilities

Manager in National Galleries of Scotland who provided access

to BMS data, Kittitach Pichetwattana, a PhD student in Centre

of Excellence in Sustainable Development Building Design,

Heriot-Watt University


REFERENCES

ASHRAE, H. (2007). Temperature and Relative Humidity

Specifications for Museum, Gallery, Library, and Archival

Collections Atlanta, United States, Heating, Ventilating, and

Air-conditioning Applications, American Society of Heating,

Refrigerating and Air-Conditioning Engineers (ASHRAE):

Chapter 21.13.

British Standard, B. (2000). Recommendations for the Storage

and Exhibition of Archival Documents BS 5454:2000

D’Agostino, D., Congedo, P. and Cataldo, R. (2013).

Computational fluid dynamics (CFD) modeling of microclimate

for salts crystallization control and artworks conservation.

Journal of Cultural Heritage.

D'Agostino, D. and Congedo, P. (2014). CFD modeling and

moisture dynamics implications of ventilation scenarios in

historical buildings. Building and Environment, 79, pp.181—

193

Eca, L. and Hoekstra, M. (2014). A procedure for the

estimation of the numerical uncertainty of CFD calculations

based on grid refinement studies. Journal of Computational

Physics, 262, pp.104—130

Harley Haddow, National Gallery Building Environmental Plant

& Control Review, Internal Report, 2011.

Sheng, M. W. (2014) Effects of renovation solutions on Energy

Saving and Indoor Environmental Quality in a historical

building, MSc dissertation, Royal Academy of Engineering

Centre of Excellence in Sustainable Development Building

Design, Heriot-Watt University.

Camuffo D, (2014) Chapter 2B – Humidity and Conservation

P77-118, Microclimate for Cultural Heritage, 2nd edition,

Wang, F., Pichetwattana, K., Hendry, R. and Galbraith, R.

(2014). Thermal performance of a gallery and refurbishment

solutions. Energy and Buildings, 71, pp.38--52.

Zhang, Y. (2014). CFD study of Skylights Refurbishment on the

indoor hygrothermal environment of a gallery space in a

historical building of cultural significance. MSc Dissertation,

Royal Academy of Engineering Centre of Excellence in

Sustainable Development Building Design, Heriot Watt

University.

APPENDIX

Appendix A1 12 scenarios

Heat gains Data BWA BWP BMA BMP BSA BSP

light (W/lamp) #1 0 23.05 0 23.05 0 23.05

Occupants (W/person) #1 0 75 0 75 0 75

Occupants vapor (g/s) #1 0 0.02 0 0.05 0 0.08 Skylight gains (kW) #2 -3.47 -2.60 -2.72 -0.58 -0.87 0.34

Roof gains (kW) #2 -2.06 -1.54 -1.61 -0.34 -0.52 0.20 Infiltration (kW) #2 -3.83 -3.20 -3.11 -1.12 -1.75 -0.67

Solar (kW) #2 0.38 1.67 1.21 3.06 5.66 8.39 Outdoor air T (°C) #4 -2.17 1.65 2.8 15.52 11.21 17.74

Room control T (°C) #3 21.04 21.04 21.66 22.29 21.83 21.83 Room control RH (%) #3 40-55 40-55 45-60 45-60 51 54.

Supply air T (°C) #4 30.81 27.18 28.05 20.3 19.3 17.35 Supply air RH (%) #4 28 31 35 41 48 57 Supply air m (kg/s) #4 0.90 0.72 0.96 1.08 0.97 2.07

Before refurbishment

Heat gains Data AWA AWP AMA AMP ASA ASP

light (W/lamp) #1 0 4.61 0 4.61 0 4.61 Occupants (W/person) #1 0 75 0 75 0 75 Occupants vapor (g/s) #1 0 0.02g/s 0 0.05g/s 0 0.08g/s

Skylight gains (kW) #2 -0.84 -0.66 -0.62 -0.47 -0.19 0.21 Roof gains (kW) #2 -1.25 -0.98 -0.92 -0.70 -0.28 0.32 Infiltration (kW) #2 0 0 0 0 0 0

Solar (kW) #2 0.33 1.45 1.05 2.66 4.93 7.31 Outdoor air T (°C) #4 6.1 7.55 6.91 7.26 13.85 20.6

Room control T (°C) #3 19.31 19.99 20.89 21.28 21.48 23.22 Room control RH (%) #3 47 47 49 51 56 55

Supply air T (°C) #4 23.91 19.3 21.59 19.3 18.89 17.29 Supply air RH (%) #4 39 49 45 48 56 54 Supply air m (kg/s) #4 0.37 0.84 0.68 1.12 1.95 1.31

After refurbishment