Stochastic Kriging for Random Simulation Metamodeling with Known Uncertainty

Authors

Wang Bo, 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;;
Gea Haechang, 2. Department of Mechanical and Aerospace Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA;;
Junqiang Bai, 3. School of Aeronautics, Northwestern Polytechnical University of China, Xi’an 710072, China;;
Yudong Zhang, 1. Research and Development Center, China Academy of Aerospace Aerodynamics, Beijing 100074, China;;
Gong Jian, 1. Research and Development Center, China Academy of Aerospace Aerodynamics, Beijing 100074, China;;
Weimin Zhang, 1. Research and Development Center, China Academy of Aerospace Aerodynamics, Beijing 100074, China;;

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.

Recommended Citation

Bo, Wang; Haechang, Gea; Bai, Junqiang; Zhang, Yudong; Jian, Gong; and Zhang, Weimin (2020) "Stochastic Kriging for Random Simulation Metamodeling with Known Uncertainty," Journal of System Simulation: Vol. 28: Iss. 6, Article 3.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss6/3

First Page

1261

Revised Date

2015-11-17

DOI Link

https://doi.org/

Last Page

1272

CLC

TP391.9

Recommended Citation

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.