Aerodynamic shape optimization using a hierarchical Genetic Algorithm

M. Sefrioui, K. Srinivas, J. Periaux

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

5 Citations (Scopus)

Abstract

This article presents several results obtained in the field of CFD optimization using Genetic Algorithms (GAs). We first introduce a new approach based on classical GAs, namely Hierarchical Genetic Algorithms (HGAs). HGAs are explained in details, and the advantages of a multi-layered hierarchical topology are clearly shown. The hierarchical topology is an excellent compromise to the exploration/exploitation dilemma often encountered by GAs. Another innovation is the introduction of multiple models for optimization problems, within the frame of an HGA. We show that with such an architecture, it is possible to use a mix of simple models (e.g. coarse meshes) that are very fast and more complex models (with slower solvers), and still achieve the same quality as that obtained with only complex models. The different concepts presented in this paper are then illustrated via experiments on a Computational Fluid Dynamics problem, namely a nozzle reconstruction. The Mach number distribution along the nozzle is solved by a time marching technique using a CUSP scheme with an iterative solver. We show the results obtained and we compare the CPU time requirements for traditional GAs, Hierarchical GAs with single model and Hierarchical GAs with multiple models. And most importantly, we show how Hierarchical GAs deal with approximate models when searching for a global solution.

Original languageEnglish
Title of host publicationEuropean Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2000
Place of PublicationBarcelona, Spain
PublisherEccOMAS
Pages1-18
Number of pages18
ISBN (Print)8489925704, 9788489925700
Publication statusPublished - 2000
EventEuropean Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2000 - Barcelona, Spain
Duration: 11 Sep 200014 Sep 2000

Other

OtherEuropean Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2000
CountrySpain
CityBarcelona
Period11/09/0014/09/00

Keywords

  • Computational fluid dynamics
  • Genetic algorithms
  • Hierarchical models
  • Optimization
  • Parallelism

Fingerprint Dive into the research topics of 'Aerodynamic shape optimization using a hierarchical Genetic Algorithm'. Together they form a unique fingerprint.

Cite this