Hostname: page-component-848d4c4894-nmvwc Total loading time: 0 Render date: 2024-07-04T21:01:03.961Z Has data issue: false hasContentIssue false

The application of Pareto methods to multidisciplinary design optimisation

Published online by Cambridge University Press:  04 July 2016

J. C. Harris
Affiliation:
Aero-Structures Department, DERA Farnborough, UK
S. V. Fenwick
Affiliation:
Aero-Structures Department, DERA Farnborough, UK

Abstract

Multidisciplinary design optimisation (MDO) provides a framework for the timely exchange of data necessary to support the highly integrated tasks typical of aerospace design. This will help reduce the duration of the design cycle and improve efficiency of the final product. Well implemented MDO capabilities will play an increasingly important role in DERA's activities to support the definition of future system requirements and the assessment of new equipment.

The framework in which an MDO approach is realised must be flexible and accommodate the diverse range of individual discipline-based tools that contribute to the overall process. This paper describes DERA's activity within the EC Framework IV ‘FRONTIER’ project to investigate the use of modern graphical user interface (GUI) methods and genetic algorithms (GAs) for the combined aerodynamic and structural design of a modern combat aircraft. The application of the techniques to identify a Pareto frontier in high level design objective space that represents the boundary beyond which improvements cannot be made without sacrificing one or other aspect of overall aircraft performance is described. The scope of the methods as an aid during the definition of system requirements and for the evaluation of trade-offs during the concept assessment stage of a project is discussed.

Type
Research Article
Copyright
Copyright © Royal Aeronautical Society 2001 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Pareto, V. General notion of economic equilibrium. Manual of Political Economy, 1971, English transaltion by Schwier, A.S., Macmillan, New York.Google Scholar
3. Poloni, C., Mosetti, G. and Contessi, S. Multi objective optimisation by gas: application to system and component design, proceedings of ECCOMAS96, Genetic Algorithms in industry, 1996, John Wiley.Google Scholar
4. Poloni, C. and Pediroda, V. GA coupled with computationally expensive simulations: tools to improve efficiency, Genetic Algorithms in Engineering and Computer Science, 1997, John Wiley.Google Scholar
5. University of Bergen Parallab. FRONTIER graphical user interface prototype version 7.1.5, December 1997.Google Scholar
6. Lovell, D.A. and Doherty, J.J. Aerodynamic design of aerofoils and wings using a constrained optimisation method, September 1994, DERA, ICAS-94-2.1.2.Google Scholar
7. Bartholomew, P. and Vinson, S. STARS: Mathematical Foundations, Software Systems for Structural Optimisation, 1993, Schittkowski, K. (Ed), H.R.E.M Hörlein, Birkhäuser Verlag, Basel.Google Scholar
8. Poloni, C. and Onesti, O. Optimisation routine prototype 4.2 functionality report and interface definition, October 1997, University of Trieste report, Frontier/UTS/ED4.2.Google Scholar
9. Fenwick, S.V. and Harris, J. C. The definition and set-up of the aero dynamic and structural problems for the FRONTIER project, May 1997, DERA report, DERA/AS/ASD/CR96381 /2,Google Scholar