Smart Structures and Systems

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Analytical and experimental exploration of sobol sequence based DoE for response estimation through hybrid simulation and polynomial chaos expansion

  • Rui Zhang (School of Civil Engineering, Shandong University) ;
  • Chengyu Yang (Key Laboratory of Concrete and Prestressed Concrete Structures of the Ministry of Education, Tongji University) ;
  • Hetao Hou (School of Civil Engineering, Shandong University) ;
  • Karlel Cornejo (School of Engineering, San Francisco State University) ;
  • Cheng Chen (School of Engineering, San Francisco State University)
  • Received : 2022.03.12
  • Accepted : 2022.10.15
  • Published : 2023.02.25
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Abstract

Hybrid simulation (HS) has attracted community attention in recent years as an efficient and effective experimental technique for structural performance evaluation in size-limited laboratories. Traditional hybrid simulations usually take deterministic properties for their numerical substructures therefore could not account for inherent uncertainties within the engineering structures to provide probabilistic performance assessment. Reliable structural performance evaluation, therefore, calls for stochastic hybrid simulation (SHS) to explicitly account for substructure uncertainties. The experimental design of SHS is explored in this study to account for uncertainties within analytical substructures. Both computational simulation and laboratory experiments are conducted to evaluate the pseudo-random Sobol sequence for the experimental design of SHS. Meta-modeling through polynomial chaos expansion (PCE) is established from a computational simulation of a nonlinear single-degree-of-freedom (SDOF) structure to evaluate the influence of nonlinear behavior and ground motions uncertainties. A series of hybrid simulations are further conducted in the laboratory to validate the findings from computational analysis. It is shown that the Sobol sequence provides a good starting point for the experimental design of stochastic hybrid simulation. However, nonlinear structural behavior involving stiffness and strength degradation could significantly increase the number of hybrid simulations to acquire accurate statistical estimation for the structural response of interests. Compared with the statistical moments calculated directly from hybrid simulations in the laboratory, the meta-model through PCE gives more accurate estimation, therefore, providing a more effective way for uncertainty quantification.

Keywords

Acknowledgement

The study has been partially supported by the Ministry of Science and Technology of the People's Republic of China under Grant No. 2018YFE0206100. The opinions and conclusions presented in this paper are those of the authors and do not necessarily reflect the views of the sponsoring organizations.

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