Evaluation of optimization algorithms for crash and NVH problems

Fabian Duddeck, Karlheinz Volz

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

4 Scopus citations

Abstract

The purpose of the studies presented here was to establish a standard optimization strategy for crash and NVH (i.e. noise, vibration, and harshness) problems. Crash simulation is a CPU consuming task, the optimization for this type of problems requires efficient strategies. The approaches should be rather general, which is inevitable for their integration into the standard design process. Monte-Carlo-search strategies, evolutionary and genetic algorithms, kriging, simulated annealing, and some methods based on regression analysis were tested. Mono- and multi-criteria optimization problems were considered. Finally, a standard strategy for optimizing is proposed and tested on a real MDO problem with five crash load cases, statics and dynamics with a finite element model of about 800,000 elements.

Original languageEnglish
Title of host publication3rd M.I.T. Conference on Computational Fluid and Solid Mechanics
Pages1240-1243
Number of pages4
StatePublished - 2005
Externally publishedYes
Event3rd M.I.T. Conference on Computational Fluid and Solid Mechanics - Boston, MA, United States
Duration: 14 Jun 200517 Jun 2005

Publication series

Name3rd M.I.T. Conference on Computational Fluid and Solid Mechanics

Conference

Conference3rd M.I.T. Conference on Computational Fluid and Solid Mechanics
Country/TerritoryUnited States
CityBoston, MA
Period14/06/0517/06/05

Keywords

  • Crashworthiness
  • Evolutionary algorithms
  • Genetic algorithms
  • Kriging
  • Multi-disciplinary optimization
  • NVH
  • Simulated annealing

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