Multidisciplinary optimization procedure for high speed aircraft using a semi-analytical sensitivity analysis procedure and multilevel decomposition

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

A multidisciplinary design optimization procedure is developed for the simultaneous improvement of sonic boom, aerodynamic and structural performance of high speed aircraft. The coupled problem is decomposed into two levels of optimization. At the first level, optimization is performed for simultaneous reduction in sonic boom and improvements in aerodynamic performance using a nonlinear programming technique. An advanced CFD solver is used to evaluate the supersonic flow field about high speed aircraft configurations. Sonic boom analysis is performed using an extrapolation procedure. The wing structural performance is improved at the second level using a hybrid optimization technique that solves the problem with both continuous and discrete design variables. The wing load carrying member, modelled as a composite box beam, is analyzed using a quasi-one-dimensional, finite element model. A discrete semi-analytical sensitivity analysis technique is employed for evaluating the aerodynamic and sonic boom design sensitivities. In both levels, the Kreisselmeier-Steinhauser function approach is used to formulate the optimization problems. Results obtained show significant improvements in the sonic boom, the aerodynamic and structural performance, compared to a reference configuration. The use of the semi-analytical sensitivity procedure for calculating aerodynamic and sonic boom sensitivities offers significant savings in computing time.

Original languageEnglish (US)
Pages (from-to)25-51
Number of pages27
JournalEngineering Optimization
Volume31
Issue number1
DOIs
StatePublished - Jan 1 1998

Keywords

  • Decomposition
  • High speed aircraft
  • Multidisciplinary optimization
  • Multiobjective optimization
  • Sensitivity analysis
  • Sonic boom

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Optimization
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

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