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Design and analysis of variable fidelity experimentation applied to engine valve heat treatment process design

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  • Deng Huang
  • Theodore T. Allen

Abstract

Summary. When experimentation on a real system is expensive, data are often collected by using cheaper, lower fidelity surrogate systems. The paper concerns response surface methods in the context of variable fidelity experimentation. We propose the use of generalized least squares to generate the predictions. We also present perhaps the first optimal designs for variable fidelity experimentation, using an extension of the expected integrated mean‐squared error criterion. Numerical tests are used to compare the performance of the method with alternatives and to investigate the robustness to incorporated assumptions. The method is applied to automotive engine valve heat treatment process design in which real world data were mixed with data from two types of computer simulation.

Suggested Citation

  • Deng Huang & Theodore T. Allen, 2005. "Design and analysis of variable fidelity experimentation applied to engine valve heat treatment process design," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(2), pages 443-463, April.
  • Handle: RePEc:bla:jorssc:v:54:y:2005:i:2:p:443-463
    DOI: 10.1111/j.1467-9876.2005.00493.x
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    Cited by:

    1. Julien Marzat & Eric Walter & Hélène Piet-Lahanier, 2013. "Worst-case global optimization of black-box functions through Kriging and relaxation," Journal of Global Optimization, Springer, vol. 55(4), pages 707-727, April.
    2. Theodore T. Allen & Olivia K. Hernand & Abdullah Alomair, 2020. "Optimal Off-line Experimentation for Games," Decision Analysis, INFORMS, vol. 17(4), pages 277-298, December.

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