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Sequential designs for sensitivity analysis of functional inputs in computer experiments

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  • Fruth, J.
  • Roustant, O.
  • Kuhnt, S.

Abstract

Computer experiments are nowadays commonly used to analyze industrial processes aiming at achieving a wanted outcome. Sensitivity analysis plays an important role in exploring the actual impact of adjustable parameters on the response variable. In this work we focus on sensitivity analysis of a scalar-valued output of a time-consuming computer code depending on scalar and functional input parameters. We investigate a sequential methodology, based on piecewise constant functions and sequential bifurcation, which is both economical and fully interpretable. The new approach is applied to a sheet metal forming problem in three sequential steps, resulting in new insights into the behavior of the forming process over time.

Suggested Citation

  • Fruth, J. & Roustant, O. & Kuhnt, S., 2015. "Sequential designs for sensitivity analysis of functional inputs in computer experiments," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 260-267.
    • Handle: RePEc:eee:reensy:v:134:y:2015:i:c:p:260-267
    DOI: 10.1016/j.ress.2014.07.018
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    References listed on IDEAS

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    1. Confalonieri, R. & Bellocchi, G. & Bregaglio, S. & Donatelli, M. & Acutis, M., 2010. "Comparison of sensitivity analysis techniques: A case study with the rice model WARM," Ecological Modelling, Elsevier, vol. 221(16), pages 1897-1906.
    2. Iooss, Bertrand & Ribatet, Mathieu, 2009. "Global sensitivity analysis of computer models with functional inputs," Reliability Engineering and System Safety, Elsevier, vol. 94(7), pages 1194-1204.
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    Cited by:

    1. Roux, Sébastien & Loisel, Patrice & Buis, Samuel, 2019. "A filter-based approach for global sensitivity analysis of models with functional inputs," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 119-128.
    2. Neves Costa, João & Ambrósio, Jorge & Andrade, António R. & Frey, Daniel, 2023. "Safety assessment using computer experiments and surrogate modeling: Railway vehicle safety and track quality indices," Reliability Engineering and System Safety, Elsevier, vol. 229(C).

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