Efficient design of experiments for sensitivity analysis based on polynomial chaos expansions

Article

Abstract

Global sensitivity analysis aims at quantifying respective effects of input random variables (or combinations thereof) onto variance of a physical or mathematical model response. Among the abundant literature on sensitivity measures, Sobol indices have received much attention since they provide accurate information for most of models. We consider a problem of experimental design points selection for Sobol’ indices estimation. Based on the concept of D-optimality, we propose a method for constructing an adaptive design of experiments, effective for calculation of Sobol’ indices based on Polynomial Chaos Expansions. We provide a set of applications that demonstrate the efficiency of the proposed approach.

Keywords

Design of experiment Sensitivity analysis Sobol indices Polynomial chaos expansions Active learning 

Mathematics Subject Classification (2010)

62K05 62K20 62J10 

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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Skolkovo Institute of Science and TechnologyMoscowRussia
  2. 2.Kharkevich Institute for Information Transmission ProblemsMoscowRussia
  3. 3.ETH Zurich, Chair of Risk, Safety and Uncertainty QuantificationZurichSwitzerland
  4. 4.National Research University Higher School of EconomicsMoscowRussia

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