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Surrogate Modeling of Computer Experiments with Different Mesh Densities

Summary: [This abstract is based on the authors' abstract.] This article considers deterministic computer experiments with real-valued tuning parameters that determine the accuracy of the numerical algorithm. A prominent example is finite-element analysis with its mesh density as the tuning parameter. The aim of this work is to integrate computer outputs with different tuning parameters. Novel non-stationary Gaussian process models are proposed to establish a framework consistent with the results in numerical analysis. Numerical studies show the advantages of the proposed method over existing methods. The methodology is illustrated with a problem in casting simulation. Supplementary material for this article is available online.

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  • Topics: Statistics
  • Keywords: Brownian motion, Kriging, Gaussian curve, Parameter design, Die casting, Shrinkage
  • Author: Tuo, Rui; Wu, C.F. Jeff; Yu, Dan;
  • Journal: Technometrics