Multi-objective aerodynamic optimization of truck deflector using genetic algorithm and CFD method

Xu Zhao, Tianshi Han, Qiuping Yang

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

Abstract

Based on the aerodynamic theory and CFD method, the single/multi-objective aerodynamic optimization design of a truck deflector is completed. During the process, two approaches have been developed separately to improve its performance; (A) a suitable cut transversely on the back yard of the circular deflector; (B) deflector reshaping using B-spline. For single-objective optimization, truck speed is fixed as the precondition, drag is set to be the objective. Moreover, the multi-objective optimization is arranged by Hybrid Genetic Algorithm (HGA), including drag and aerodynamic acoustics. This research indicates that both approaches can improve the local flow status, and provide a better characteristics in reducing drag (4. 50%-6. 23% and 3.16%-4. 03% respectively) and acoustics, which is valuable both in academic research practical application.

Original languageEnglish
Title of host publicationProceedings of 2010 Asia-Pacific International Symposium on Aerospace Technology, APISAT 2010
PublisherNorthwestern Polytechnical University
Pages432-434
Number of pages3
ISBN (Electronic)9787561228999
StatePublished - 2010
Event2010 Asia-Pacific International Symposium on Aerospace Technology, APISAT 2010 - Xi'an, China
Duration: 13 Sep 201015 Sep 2010

Publication series

NameProceedings of 2010 Asia-Pacific International Symposium on Aerospace Technology, APISAT 2010

Conference

Conference2010 Asia-Pacific International Symposium on Aerospace Technology, APISAT 2010
Country/TerritoryChina
CityXi'an
Period13/09/1015/09/10

Keywords

  • Aerodynamic acoustics
  • CFD
  • Drag
  • Erspline
  • Hybrid genetic algorithm

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