On using kriging models as probabilistic models in design

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Kriging models are frequently used as metamodels during system design optimization. In many applications, a kriging model is used as a deterministic model of a computationally expensive analysis or simulation. In this paper, a kriging model is employed as a probabilistic model on a one-dimensional and two two-dimensional test problems. A probabilistic model is a model in which the parameters are random variables resulting in a probability distribution of the output rather than a deterministic value. A probabilistic model can be used in design to quantify the knowledge designers have about a subsystem and the lack of knowledge or uncertainty in the model. Using a kriging model as a probabilistic model requires that the correlation of observations is only a function of the distance between the observations and that the observations have a Gaussian probability distribution. This paper will provide some methods to satisfy these requirements when using kriging models as probabilistic models.

Original languageEnglish (US)
Title of host publication2004 SAE World Congress
DOIs
StatePublished - Dec 1 2004
Event2004 SAE World Congress - Detroit, MI, United States
Duration: Mar 8 2004Mar 11 2004

Other

Other2004 SAE World Congress
CountryUnited States
CityDetroit, MI
Period3/8/043/11/04

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All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering

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