Study of improved multiple discipline feasible strategy for complicated system optimization

Teng Long*, Li Liu, Huaijian Li

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

The advantages of global sensitivity equation (GSE) method are firstly pointed out, with which an improved multiple discipline feasible (MDF) strategy based on GSE, denoted as MDF-GSE, is developed. In MDF-GSE strategy, the sensitivity of complicated coupled system is calculated using GSE in a parallel manner, which makes MDF-GSE more efficiency when optimizing complicated coupled system compared with the original MDF strategy. Additionally, the preferable performance in convergence and robustness of MDF is also inherited in MDF-GSE. A conceptual optimization of a training airplane is executed using both MDF and MDF-GSE. The results of quantificational comparison demonstrate that computational efficiency is improved dramatically by using MDF-GSE, which makes required computation cost decreased by about 86%. The optimization time, furthermore, ulteriorly reduced due to the quasi-parallel capability of MDF-GSE. It is indicated that the MDF-GSE strategy can enhance the optimization efficiency for the complicated coupled systems.

Original languageEnglish
Title of host publicationFrontiers of Manufacturing and Design Science
Pages3264-3268
Number of pages5
DOIs
Publication statusPublished - 2011
Event2010 International Conference on Frontiers of Manufacturing and Design Science, ICFMD2010 - Chongqing, China
Duration: 11 Dec 201012 Dec 2010

Publication series

NameApplied Mechanics and Materials
Volume44-47
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference2010 International Conference on Frontiers of Manufacturing and Design Science, ICFMD2010
Country/TerritoryChina
CityChongqing
Period11/12/1012/12/10

Keywords

  • Global sensitivity equation
  • MDO strategy
  • Multiple disciplinary feasible strategy
  • Optimization

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