An ensemble approach for model bias prediction

Zhimin Xi, Yan Fu, Ren Jye Yang

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Model validation is a process of determining the degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model. In reliability based design, the intended use of the model is to identify an optimal design with the minimum cost function while satisfying all reliability constraints. It is pivotal that computational models should be validated before conducting the reliability based design. This paper presents an ensemble approach for model bias prediction in order to correct predictions of computational models. The basic idea is to first characterize the model bias of computational models, then correct the model prediction by adding the characterized model bias. The ensemble approach is composed of two prediction mechanisms: 1) response surface of model bias, and 2) Copula modeling of a series of relationships between design variables and the model bias, between model prediction and the model bias. Advantages of both mechanisms are utilized with an accuracy based weighting approach. A vehicle design of front impact example is used to demonstrate the effectiveness of the proposed methodology.

Original languageEnglish (US)
JournalSAE International Journal of Materials and Manufacturing
Volume6
Issue number3
DOIs
StatePublished - Apr 2013
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Mechanics of Materials
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

Keywords

  • Copula
  • Model bias prediction
  • Model validation
  • Reliability based design

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