tera2020 - rationale, objectives and design algorithm

European Workshop on New Aero Engine ConceptsMunich, 30 June – 1 July 2010

TERA2020 – Rationale, Objectives and Design Algorithm

NEWAC is an Integrated Project Co-funded by the European Commission within the Sixth Framework Programme(2002-2006) under Thematic Priority 4 Aeronautics and Space.

Konstantinos Kyprianidis, Cranfield University

Contributors: Bernhard Lehmayr, University of Stuttgart Alexios Alexiou, National Technical University of AthensLei Xu, Chalmers University


Contents

• What is TERA2020?

• Which partners are involved?

• How does TERA2020 work?

• What kind of studies can TERA2020 be used for?


• What kind of studies can TERA2020 be used for?

• Conclusions and Outlook


What is TERA2020?

• A multi-disciplinary tool for aero engine conceptual design.

• Developed by universities in the EU collaborative projects VITAL, NEWAC and DREAM projects for over 6 years.

• Incorporates significant feedback from industry.


• Incorporates significant feedback from industry.

• Demonstrated as an effective tool in NEWAC for sensitivity analysis, parametric studies and optimisation of the study engines.

• It is not an expert system, so it still requires the user to have a good under-standing of engine performance and design and knowledge of the capabilities of the new technologies available for each engine.


VITAL/NEWAC/DREAM TERA2020 – Core Partners



VITAL/NEWAC/DREAM TERA2020 – Contributions

• Substantial amount of the knowledge used in TERA2020 has been generated in previous research projects.



NEWAC TERA2020 – Partners in SP1 and WP1.3



1

24

TERA2020 Algorithm

1) PERFORMANCE

2) WEI(CO)

3) (WEI)CO


3

5

6

7

4) HERMES

5) HEPHAESTUS

6) NOISE

7) ECONOMICS


• The developed tool is targeted towards identifying an appropriate design space

where more complex and time-consuming tools could be utilised.

• In many cases the modelling carried out is based on correlations that are

available in the public domain or have been supplied by original equipment

Methods and validity


manufacturers within the European collaborative projects VITAL and NEWAC.

• It is recognized that such correlations have a limited range of validity and are

dependent on supporting engineering science base.

• As an appropriate design space is defined, a more rigorous iterative design

procedure would typically be set involving a large number of company specialists.


TERA2020 design parameters

• W2 (Fan mass flow)

• Fan pressure ratio

• Fan 2 pressure ratio (CRFC)

• W23 (Core mass flow)

• Booster/IPC pressure ratio

• HPC pressure ratio

• Engine weight

• SFC and block fuel (business case)

• LTO NOx and margin against CAEP/6

• Cumulative noise margin

• Production cost

Main Design Parameters Typical Responses


• HPT NGV cooling mass flow ratio

• T40 for take-off rating

• T40 for climb rating

• T40 for cruise rating (GTIR)

• Low pressure turbine variable guide vane angle for take-off and cruise rating (GTIR)

• IC effectiveness for take-off rating (DDIC)

• IC/ACAC effectiveness for climb rating

(DDIC, GTAC,GTIR)

• IC effectiveness for cruise rating (DDIC)

• IC mass flow ratio (Wcold/Whot) (DDIC, GTIR)

• Recuperator effectiveness (GTIR)

• Maintenance DOC

• Direct operating costs

• FAR take-off field length and time to height

• HPT metal temperature at take-off, climb and cruise (GTIR), LPT outlet temperature (GTIR) and time between overhaul

• Compressor delivery temperature at take-off

• HPC blade height

Typical Constraints


Engine optimisation process



21.5

2222

22

22.5

22.5

9

966

968

970

972

974

974

wvs

.no

min

alin

%

-13

-12Rel. fuel burn

0.9810.980.9790.9780.9770.9760.9750.9740.9730.972

Climb time [min]T30 [K]

What kind of studies can TERA2020 be used for?


22.5

23

23

23.5

23.5966

966

968

970

972

Fan pressure ratio vs. nominal in %C

ore

mas

sflo

w-6 -5 -4 -3

-15

-14

0.9720.9710.970.9690.9680.967

• TERA2020 may be utilised for a varietyof studies � sensitivity analysis, cycleoptimisation, engine/aircraft matching…(more on next presentation!)


Conclusions

• Overall TERA2020 has progressed well and has met its NEWAC targets.

• TERA2020 is targeted towards identifying an appropriate design space where more complex and time-consuming tools could be utilised. Results produced can give useful insight on novel concepts.


• TERA2020 enables technology assessment within collaborative pre-competitive studies to be broadened to consider additional factors such as economics and environmental impact.

• The tool is most useful for rapid optimization and ‘what if’ studies about a well worked-up design.

• TERA2020 optimisation studies indicate further potential from the NEWAC innovative concepts in terms of block fuel (more on next presentation!)


Outlook

• Further TERA2020 work to be carried out during the NEWAC prolongation

• Work focuses on 3 new configurations– Geared Turbofan configuration with Intercooled Core for Long Range

applications (GTICLR)– Geared Turbofan configuration with Active Core for Short Range


– Geared Turbofan configuration with Active Core for Short Range applications (GTACSR) at higher OPR (ACAC as enabler) and with unconventional heat management aspects

– Contra-Rotating turbofan configuration with Contra-Rotating core for Long Range applications (CRCRLR)



Back up slides


• Archive based Micro Genetic Algorithm (AMGA)

• Adaptive Simulated Annealing (ASA)

• Downhill Simplex

• Hooke-Jeeves

• Large Scale Generalized Reduced Gradient (LSGRG)

Optimisation methods available


• Large Scale Generalized Reduced Gradient (LSGRG)

• Modified Method of Feasible Directions (MMFD)

• Multifunction Optimization System Tool (MOST)

• Multi-Island Genetic Algorithm

• Neighborhood Cultivation Genetic Algorithm (NCGA)

• Sequential Quadratic Programming (NLPQL)

• Non-dominated Sorting Genetic Algorithm (NCGA-II)

• Pointer Automatic Optimizer

• Stress Ratio Optimizer


Engine performance module



Weight (Wei) and Cost (Co) module



Economic parameters and risk analysis

• Fuel price, exchange rates, interestrates and inflation vary over theyears


• Probabilistic methods are applied inTERA to consider the volatility ofvarious economic parameters over along time period.

Source: International Air Transport Association, 2010, http://www.iata.org/Platts, 2010, http://www.platts.com/


Working with iSIGHT FD:

The reality:

Every predefined

TERA2020 integration


Every predefined engine configurationimplies immense effortto correctly define andlink all variables.

tera2020 - rationale, objectives and design algorithm

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