Stochastic Kriging for Random Simulation Metamodeling with Known Uncertainty

Journal of System Simulation ›› 2016, Vol. 28 ›› Issue (6): 1261-1272.

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Stochastic Kriging for Random Simulation Metamodeling with Known Uncertainty

Wang Bo^{1, 2}, Gea Haechang², Bai Junqiang³, Zhang Yudong¹, Gong Jian¹, Zhang Weimin¹

1. Research and Development Center, China Academy of Aerospace Aerodynamics, Beijing 100074, China;
2. Department of Mechanical and Aerospace Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA;
3. School of Aeronautics, Northwestern Polytechnical University of China, Xi’an 710072, China;

Received:2015-07-08 Revised:2015-11-17 Online:2016-06-08 Published:2020-06-08
About author:Wang Bo(1984-), Gender: Male, Born in Neihuang, China, Han nationality, Degree: Doctor, Interest: Metamodeling, Aircraft Design, CFD. Haechang Gea, Gender: Male, Degree: Doctor, Interest: Optimization, Uncertainty.
Supported by:
National Natural Science Foundation of China (11302213)

Abstract

Abstract: Uncertainty-based design has been widely carried out these years. In order to deal with the problems with large amount of calculation, a stochastic kriging for random simulation metamodeling with known uncertainty was derived, which firstly included intrinsic uncertainty in metamodel initial formulation to fully account for inputs uncertainty, and then incorporated the correlationships of intrinsic uncertainty among all observed points. Several examples with known uncertainty were also conducted, in which the proposed method shows much better variance predictions than other similar methods. Simulation results show the proposed method is a more general form of kriging, which can also widely deal with the uncertainty-based problems with heterogeneous variances as a stochastic metamodel.

Key words: stochastic problems, uncertainty estimation, metamodeling, kriging method

CLC Number:

TP391.9

Wang Bo, Gea Haechang, Bai Junqiang, Zhang Yudong, Gong Jian, Zhang Weimin. Stochastic Kriging for Random Simulation Metamodeling with Known Uncertainty[J]. Journal of System Simulation, 2016, 28(6): 1261-1272.

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Stochastic Kriging for Random Simulation Metamodeling with Known Uncertainty

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