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Multidisciplinary design and optimisation of conceptual rotorcraft powerplants for operational performance and environmental impact

Published online by Cambridge University Press:  27 January 2016

F. Ali ,
K. Tzanidakis ,
I. Goulos ,
V. Pachidis  and
R. d’Ippolito
F. Ali
Affiliation:
Propulsion Engineering Centre, School of Aerospace, Transport and Manufacturing, Cranfield University, Bedford, UK
K. Tzanidakis
Affiliation:
Propulsion Engineering Centre, School of Aerospace, Transport and Manufacturing, Cranfield University, Bedford, UK
I. Goulos
Affiliation:
Propulsion Engineering Centre, School of Aerospace, Transport and Manufacturing, Cranfield University, Bedford, UK
V. Pachidis
Affiliation:
Propulsion Engineering Centre, School of Aerospace, Transport and Manufacturing, Cranfield University, Bedford, UK
R. d’Ippolito
Affiliation:
Noesis Solutions, Belgium
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Abstract

This paper demonstrates the application of an integrated rotorcraft multidisciplinary design and optimisation framework, deployed for the purpose of preliminary design and assessment of optimum regenerative powerplant configurations for rotorcraft applications. The proposed approach comprises a wide-range of individual modelling theories applicable to rotorcraft flight dynamics, gas turbine engine performance and weight estimation as well as a physics-based stirred reactor model, for the rapid estimation of various gas turbine gaseous emissions. A single-objective Particle Swarm Optimiser is coupled with the aforementioned rotorcraft design framework. The overall methodology is deployed for the design and optimisation of a reference multipurpose Twin-Engine-Light civil rotorcraft, modelled after the Bo105 helicopter, which employs two Rolls-Royce Allison 250-C20B turboshaft engines. Through the implementation of a single-objective optimisation strategy, notionally based optimum engine design configurations are acquired in terms of engine weight, mission fuel burn and mission gaseous emissions inventory at constant technology level.

The acquired optimum regenerative engine configurations are subsequently deployed for the design of conceptual rotorcraft regenerative engine configurations, targeting improved mission fuel economy, enhanced payload-range capability as well as overall environmental impact, while maintaining the respective rotorcraft airworthiness requirements. The proposed methodology essentially constitutes as an enabler for designing rotorcraft powerplants within realistic, three-dimensional operations and towards realising their associated design trade-offs at mission level.

Type
Research Article
Information
The Aeronautical Journal , Volume 119 , Issue 1217 , July 2015 , pp. 891 - 914
Copyright
Copyright © Royal Aeronautical Society 2015

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References

1.Kenneth, M.R.A prospective, the importance of propulsion technology to the development of helicopter systems with a vision for the future The 27th Alexander A. Nikolsky Lecture, J American Helicopter Society, 1 October 2008, 53, (4), pp 307–337(31).Google Scholar
2.Richard, D.S. Research requirements for development of regenerative engines for helicopters, NASA technical report, NASA CR-145112.Google Scholar
3.McDonald, F.C., Massardo, F.A., Rodgers, C. and Stone, A.Regenerated gas turbine aero-engines. Part I: Early development activities, aircraft engineering and aerospace technology, 80, (2), pp 139–157.Google Scholar
4.McDonald, F.C., Massardo, F.A., Rodgers, C. and Stone, A.Regenerated gas turbine aero-engines. Part II: engine design studies following early development testing, Aircraft Engineering and Aerospace Technology, 80, (3), pp 280 – 294.Google Scholar
5.McDonald, F.C., Massardo, F. A., Rodgers, C. and Stone, A.Regenerated gas turbine aero-engines. Part III: engine concepts for reduced emissions, lower fuel consumption and noise abatement, Aircraft Engineering and Aerospace Technology, 80, (4), pp 408–426.CrossRefGoogle Scholar
6. Advisory Council for Aeronautics Research in Europe Report, Strategic Research Agenda, 1, October 2002.Google Scholar
7. Clean Sky, Green Rotorcraft ITD Publishable Report P6, 1 January to 31 December, 2013.Google Scholar
8.D’ippolito, R., Stevens, J., Pachidis, V., Berta, A., Goulos, I. and Rizzi, C. A Multidisciplinary Simulation Framework for Optimization of Rotorcraft Operations and Evironmental Impact, Second International Conference on Engineering Optimization, 2012.Google Scholar
9.Clarke, J.P.The role of advanced air traffic management in reducing the impact of aircraft noise and enabling aviation growth, J Air Transp. Manag, 9, pp 161–165.CrossRefGoogle Scholar
10.Brooker, P.Civil aircraft design priorities: air quality? climate change? noise?, Aeronaut J, 2006, 110, (1110), pp 517–532.CrossRefGoogle Scholar
11.Goulos, I., Pachidis, V., D’ippolito, R., Stevens, J. and Smith, C.An integrated approach for the multidisciplinary design of optimum rotorcraft operations, ASME J Eng Gas Turbines Power, 2012, 134, (9), p 091701.CrossRefGoogle Scholar
12.Linares, C., Lawson, C.P. and Smith, H., Multidisciplinary optimisation framework for minimum rotorcraft fuel and air pollutants at mission level, Aeronaut J, July 2013, 117, (1193).CrossRefGoogle Scholar
13.Goulos, I., Fabian, H., Vishal, S., Pachidis, V., D’ippolito, R. and Massimo, D.Rotorcraft engine cycle optimization at mission level, Asme J. Eng Gas Turbines Power, 135, (9), p 091202–1.CrossRefGoogle Scholar
14.Cohen, H., Rogers, G.F.C., Saravanamouttoo, Hih. 1996, Gas turbine theory 4th ed, Padstow, Cornwall, UK.Google Scholar
15.Ali, F., Goulos, I. and Pachidis, V.Helicopter mission analysis for a recuperated turboshaft engine. Proceedings of ASME Turbo Expo 2013: Power for L and Sea and Air, 3-7 June, 2013, San Antonio, Texas, USA.Google Scholar
16.Ohanian, O.J., Paul, A.G., Adam, L.E., Christopher, R.D. and Christian, R.S.Vehicle-level optimisation of rotorcraft propulsion systems Proceedings of American Helicopter Society, 70th Annual Forum and Technology Display, 20-22 May 2014, Montreal, Canada.Google Scholar
17.Johnson, W.Rotorcraft conceptual design environment Proceeding of the 2nd International Forum on Rotorcraft Multidisciplinary Technology, Seoul, Korea, 19-20 October, 2009.Google Scholar
18.Lytle, K.J. The numerical propulsion system: An overview NASA Technical Report: NASA/TM-2000-209915.Google Scholar
19.Avera, M. and Singh, R.OpenMDAO/NDARC framework for assessing performance impact of rotor technology integration, Proceedings of American Helicopter Society, 70th Annual Forum and Technology Display, 20-22 May 2014, Montreal, Canada.Google Scholar
20.Ali, F., Goulos, I. and Pachidis, V.An integrated methodology to assess the operational and environmental performance of a conceptual regenerative helicopter, Aeronaut J, January 2015, 119, (1211).CrossRefGoogle Scholar
21. Noesis Solutions, (2012), Optimus ReV 10.6 Manual, Leuven, Belgium.Google Scholar
22.Tzanidakis, K., Pachidis, V., D’ippolito, R. and D’auria, M.Optimisation in a multidisciplinary environment – a turbomachinery application, NAFEMS World Congress, 9-12 June 2013, Salzburg, Austria.Google Scholar
23.Iman, R.L.Latin Hypercube Sampling, John Wiley & Sons.Google Scholar
24.Kleijnen, J.P.Kriging metamodelling in simulation: a review, European Journal of Operational Research, 192, (3), pp 707–716.CrossRefGoogle Scholar
25.Wang, G.G. and Shan, S.Review of metamodelling techniques in support of engineering design optimization, J of Mechanical Design, 129, (370).Google Scholar
26.Goulos, I., Giannakakis, P., Pachidis, V. and Pilidis, P.Mission performance simulation of integrated helicopter–engine systems using an aeroelastic rotor model, ASME J Eng Gas Turbines Power, 135, (9), 091201-1.Google Scholar
27.Goulos, I., Pachidis, V. and Pilidis, P.Lagrangian formulation for the rapid estimation of helicopter rotor blade vibration characteristics, Aeronaut J, August 2014, 118, (1206).CrossRefGoogle Scholar
28.Goulos, I. and Pachidis, V.Real-time aeroelasticity simulation of open rotor with slender blades for the multidisciplinary design of rotorcraft, ASME J Eng. Gas Turbines and Power, January 2015, 137, (1).CrossRefGoogle Scholar
29.Goulos, I., Pachidis, V. and Pilidis, P.Helicopter rotor blade flexibility simulation for aeroelasticity and flight dynamics applications, J Am Helicopter Soc, J American Helicopter Society, October 2014, 59, (4).Google Scholar
30.Pachidis, V., Pilidis, P., Marinai, L. and TemplAlexis, I.Towards a full two dimensional gas turbine performance simulator, Aeronaut J, 2007, 111, (1121), pp 433–442.CrossRefGoogle Scholar
31.Li, Y.G., Marinai, L., Gatto, E.L., Pachidis, V. and Pilidis, P.Multiple-point adaptive performance simulation tuned to aeroengine test-bed data, J Propulsion and Power, 2009, 25, (3), pp 635–641.CrossRefGoogle Scholar
32.Goulos, I., Ali, F., Tzanidakis, K., Pachidis, V. and D’ippolito, R.A multidisciplinary approach for the comprehensive assessment of integrated rotorcraft-powerplant systems, ASME J Eng Gas Turbines and Power, January 2015, 137, (1).CrossRefGoogle Scholar
33.Nicolas, C.K.Increased helicopter capability through advanced power plant technology, Journal of the American Helicopter Society, 12, (3), pp 1–15(15).Google Scholar
34.Lolis, P., Giannakakis, P., Sethi, V., Jackson, A.J.B. and Pilidis, P.Evaluation of aero gas turbine preliminary weight estimation methods, Aeronaut J, June 2014, 118, (1204).CrossRefGoogle Scholar
35. Jane’s International Aero-Engines, Aircraft Engines of the World, 20, pp 260–261.Google Scholar
36.Jack, D.M., William, H.H. and David, T.P.Aircraft Engine Design 2nd ed, Virginia: AIAA, 2002.Google Scholar
37.Deb, K.Multi-objective genetic algorithms: Problem diffculties and construction of test problems, Evolutionary Computation, 7, (3), pp 205–230.CrossRefGoogle Scholar
38.Goulos, I., Pachidis, V. and Pilidis, P.Flexible rotor blade dynamics for helicopter aeromechanics including comparisons with experimental data, Aeronaut J, March 2015, 119, (1213), pp 301–342.CrossRefGoogle Scholar