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On Using Kriging Models as Probabilistic Models in Design Pennsylvania State University

SAE Technical Papers (1906-current) Available online

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Format:
Conference/Event
Author/Creator:
Martin, Jay D., author.
Conference Name:
SAE 2004 World Congress & Exhibition (2004-03-08 : Detroit, Michigan, United States)
Language:
English
Physical Description:
1 online resource
Place of Publication:
Warrendale, PA SAE International 2004
Summary:
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
Notes:
Vendor supplied data
Publisher Number:
2004-01-0430
Access Restriction:
Restricted for use by site license

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