System reliability based vehicle design for crashworthiness and effects of various uncertainty reduction measures

Erdem Acar, Kiran Solanki

Research output: Contribution to journalArticle

39 Citations (Scopus)

Abstract

Reliability-based design optimization of automobile structures for crashworthiness has been studied by many researchers by using either single component probabilistic constraints or single failure mode based probabilistic constraints, while system reliability considerations are mostly disregarded. In this paper, we perform system reliability based design optimization (SRBDO) of an automobile for crashworthiness and analyze the effect of reliability allocation in different failure modes. In addition, effects of various uncertainty reduction measures (e.g., reducing variability in material properties, reducing error of finite element analysis) are investigated and tradeoff plots of uncertainty reduction, system reliability and structural weight are generated. These types of tradeoff plots can be used by a company manager to decide whether to allocate the company resources for employing uncertainty reduction measures or allocating the resources for the excess weight to protect against the unreduced uncertainties. Furthermore, relative importance of automobile structural members in different crash scenarios is quantified.

Original languageEnglish (US)
Pages (from-to)311-325
Number of pages15
JournalStructural and Multidisciplinary Optimization
Volume39
Issue number3
DOIs
StatePublished - Sep 2009
Externally publishedYes

Fingerprint

Crashworthiness
System Reliability
Automobile
Probabilistic Constraints
Uncertainty
Automobiles
Failure Mode
Trade-offs
Failure modes
Resources
Crash
Material Properties
Structural members
Excess
Finite Element
Industry
Materials properties
Managers
Scenarios
Design

Keywords

  • Automobile crashworthiness
  • System reliability
  • Uncertainty reduction
  • Weight saving

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Control and Systems Engineering
  • Control and Optimization

Cite this

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