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Authors
Xu, Can
Liu, Zhao
Zhu, Ping
Li, Mushi
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Funding
Funding for this research was provided by:
Key National Natural Science Foundation of China (U1864211)
National Natural Science Foundation of China (11772191)
National Science Foundation for Young Scientists of China (51705312)
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Article History
Received: 10 January 2020
Revised: 2 May 2020
Accepted: 29 June 2020
First Online: 24 July 2020
Compliance with ethical standards
:
: The authors declare that they have no conflict of interest.
: The pseudocodes for the algorithms intended to facilitate the replication of results are provided in this section. The pseudocode of the M-MCS is presented below.The pseudocode of PCE-quantification for multilevel metamodel uncertainty is presented below.The pseudocode of the proposed adaptive sequential sampling strategy is presented below.The toolbox SURROGATES is free software, which can be learned about through the website (). The toolbox is employed to build the Kriging model using the following parameters: the correlation model is “corrgauss,” the regression model is “regpoly0,” the initial guess on “theta” is 0.5. The toolbox UQLab is completely free for academic users (). And the toolbox is used to construct the PCE models by the following parameters: the method is “LARS,” the hyperbolic norm is 1. The optimization is executed by MATLAB genetic algorithm tool with the following parameters: the “Generations” is 100, the “PopulationSize” is 100. The code for random filed representation is downloaded from the website (<u>)</u>. Other related parameters for replicating this paper have been provided in Section .In order to further understand the proposed strategy and replicate the results presented in this paper, the MATLAB codes for examples 1~2 are provided as the supplementary material. Table listed the basic information of the code files. The results of numerical examples can be obtained by running the main programs, and the following subprograms need to be called while running the main programs. It should be note that the results of each run will vary depending on the initial samples generated based on the LHS method. Therefore, the attachment also provides the data set that obtains the figures in this article.
