首页|Dimension-independent single-loop Monte Carlo simulation method for estimate of Sobol' indices in variance-based sensitivity analysis
Dimension-independent single-loop Monte Carlo simulation method for estimate of Sobol' indices in variance-based sensitivity analysis
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NETL
NSTL
Elsevier
This contribution presents a novel approach for estimating the Sobol' index, which has been commonly employed in variance-based sensitivity analysis of computational models that may often involve multiple uncertain parameters. Specifically, a single-loop Monte Carlo simulation (MCS) method, which is independent of the dimensionality of inputs, is proposed to reduce the computational cost of complicated models. proposed method is realized by developing a new estimator of the Sobol' index computed via the twodimensional kernel density estimation, which can be easy programming while ensuring high accuracy. Numerical examples are studied to demonstrate the advantages of the proposed method.
Uncertainty quantificationMonte Carlo simulationVariance-based sensitivity analysisKernel density estimationMODELS
Wan, Zhiqiang、Wang, Silong、Wu, Ziyan、Wang, Xiuli
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Northwestern Polytechnical University School of Mechanics Civil Engineering and Architecture||Leibniz University Hannover Faculty of Civil Engineering and Geodetic Science
Northwestern Polytechnical University School of Mechanics Civil Engineering and Architecture
NETL
NSTL
Elsevier
