Abstract
In this paper we present an approach for preliminary aero engine design with the overall goal to improve the core engine with regards to efficiency and emissions. This is achieved through the usage of a cascaded multi-criterion global optimization strategy, where the overall optimization is performed on the basis of decoupled black box sub-optimization of components. Such an approach has the advantage to cut down the number of design variables for each optimization problem involved and to use legacy code for components.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Adelman HM, Haftka RT (1986) Sensitivity analysis of discrete structural systems. AIAA J 24(5):823–832
Angersbach A, Bestle D (2014) Optimization of air distribution in a preliminary design stage of an aero-engine combustor. In: 14th AIAA aviation technology, integration, and operations conference, AIAA AVIATION Forum. American Institute of Aeronautics and Astronautics
Bouhamidi A, Méhauté AL (2004) Radial basis functions under tension. J Approximation Theory 127(2):135–154
Dalbey K, Karystinos G (2010) Fast generation of space-filling Latin hypercube sample designs. In: 13th AIAA/ISSMO multidisciplinary analysis optimization conference, vol 2010-9085
Hansen N (2006) The CMA evolution strategy: a comparing review. Springer, Berlin, pp 75–102
ICAO Airport Air Quality Manual (2011) http://www.icao.int/environmental-protection/Documents/Publications/FINAL.Doc%209889.Corrigendum.en.PDF. Accessed 15 Mar 2017
Lockan M, Bestle D, Janke C, Meyer M (2017) Optimization of coupled system components using approximations of interface quantities. In: Proceedings of the ASME Turbo Expo 2017: turbine technical conference and exposition, Charlotte, pp. GT 2017–64,135
Pöhlmann F (2015) Optimization and coupling strategies for codes of different fidelity to automate an aerodynamic compressor design process. PhD thesis, Brandenburg University of Technology, Shaker, Aachen
Regis RG, Shoemaker CA (2007) A stochastic radial basis function method for the global optimization of expensive functions. INFORMS J Comput 19(4):497–509
Sellar R, Batill S, Renaud J (1996) Response surface based, concurrent subspace optimization for multidisciplinary system design. In: 34th aerospace sciences meeting and exhibit, p 714
Sobieszczanski-Sobieski J (1989) Optimization by decomposition: a step from hierarchic to non-hierarchic systems. NASA STI/Recon Technical Report N 89
Sobieszczanski-Sobieski J, Agte JS, Sandusky R (1998) Bi-level integrated system synthesis. NASA Technical Memorandum 1998-208715
Sobieszczanski-Sobieski J, Altus TD, Phillips M, Sandusky R (2003) Bilevel integrated system synthesis for concurrent and distributed processing. AIAA J 41(10):1996–2003
Acknowledgements
This work has been carried out in collaboration with Rolls-Royce Deutschland as part of the research project VITIV (Virtual Turbomachinery, Proj.-No. 80164702) funded by the State of Brandenburg, the European Regional Development Fund, and Rolls-Royce Deutschland. Rolls-Royce Deutschlands permission to publish this work is greatly acknowledged.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
Extra, S., Lockan, M., Bestle, D., Flassig, P. (2019). Coupled Subsystem Optimization for Preliminary Core Engine Design. In: Andrés-Pérez, E., González, L., Periaux, J., Gauger, N., Quagliarella, D., Giannakoglou, K. (eds) Evolutionary and Deterministic Methods for Design Optimization and Control With Applications to Industrial and Societal Problems. Computational Methods in Applied Sciences, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-319-89890-2_33
Download citation
DOI: https://doi.org/10.1007/978-3-319-89890-2_33
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-89889-6
Online ISBN: 978-3-319-89890-2
eBook Packages: EngineeringEngineering (R0)