设计理论与方法学 |
|
|
|
|
基于Stochastic Kriging模型的不确定性序贯试验设计方法 |
王波1, GEA Haechang2, 白俊强3, 张玉东1, 宫建1, 张卫民1 |
1. 中国航天空气动力技术研究院 研发中心, 北京 100074;
2. 新泽西州立大学 机械宇航学院, 新泽西 Piscataway, 08854;
3. 西北工业大学 航空学院, 陕西 西安 710072 |
|
The uncertainty-based sequential design of experiment method based on Stochastic Kriging metamodel |
WANG Bo1, GEA Haechang2, BAI Jun-qiang3, ZHANG Yu-dong1, GONG Jian1, ZHANG Wei-min1 |
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;
3. School of Aeronautics, Northwestern Polytechnical University of China, Xi'an 710072, China |
引用本文:
王波, GEA Haechang, 白俊强, 张玉东, 宫建, 张卫民. 基于Stochastic Kriging模型的不确定性序贯试验设计方法[J]. 工程设计学报, 2016, 23(6): 530-536.
WANG Bo, GEA Haechang, BAI Jun-qiang, ZHANG Yu-dong, GONG Jian, ZHANG Wei-min. The uncertainty-based sequential design of experiment method based on Stochastic Kriging metamodel. Chinese Journal of Engineering Design, 2016, 23(6): 530-536.
链接本文:
https://www.zjujournals.com/gcsjxb/CN/10.3785/j.issn.1006-754X.2016.06.002
或
https://www.zjujournals.com/gcsjxb/CN/Y2016/V23/I6/530
|
[1] ZANG T A, HEMSCH M J, HILBURGER M W. et al. Needs and opportunities for uncertainty-based multidisciplinary design methods for aerospace vehicles[R/OL].[2016-11-02]. http://www.cs.odu.edu/~mln/ltrs-pdfs/NASA-2002-tm211462.pdf.
[2] SLOTNICK J, KHODADOUST A, ALONSO J, et al. CFD vision 2030 study:a path to revolutionary computational aerosciences[R/OL].[2016-11-02]. https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20140003093.pdf.
[3] BLATTNIG S R, LUCKRING J M, JOSEPH H M, et al. NASA standard for models and simulations:philosophy and requirements overview[J]. Journal of Aircraft, 2012, 50(1):20-28.
[4] Editorial policy statement on numerical and experimental accuracy[J/OL].[2015-07-06]. http://servidor.demec.ufpr.br/CFD/bibliografia/erros_numericos/AIAA_Journals_NumericalAccuracy.pdf.
[5] MURTHY J Y, MATHUR S R. Computational heat transfer in complex systems:a review of needs and opportunities[J]. Journal of Heat Transfer, 2012, 134(3):031016.
[6] RAZAVI S, TOLSON B A, BURN D H. Review of surrogate modeling in water resources[J]. Water Resources Research, 2012, 48(7):107-116.
[7] XUE Z, MARCHI M, PARASHAR S, et al. Comparing uncertainty quantification with polynomial chaos and metamodels-based strategies for computationally expensive CAE simulations and optimization applications[R/OL].[2016-11-02]. http://papers.sae.org/2015-01-0437/.
[8] GHANEM R, SPANOS P. Stochastic finite elements:a spectral approach[M]. New York:Courier Dover Publications, 2003.
[9] WANG Bo, BAI Jun-qiang. GEA Haechang. Stochastic kriging for random simulation metamodeling with finite sampling[C]. 39th ASME Design Automation Conference, Portland, Oregon, Aug. 5-8, 2013.
[10] VOLPI S, DIEZ M, GAUL N J, et al. Development and validation of a dynamic metamodel based on stochastic radial basis functions and uncertainty quantification[J]. Structural Multidisciplinary Optimization. 2015,51(2):347-368.
[11] SANCHEZ S M. Work smarter, not harder:guidelines for designing simulation experiments[C]//Proceedings of the 2005 Winter Simulation Conference. Orlando, FLorida, Dec. 4-7, 2005:69-82.
[12] KOEHLER J R, OWEN A B. Computer experiments[M]. Pennsylvania:Handbook of Statistics, 1996:261-308.
[13] RIDGE E. KUDENKO D. Sequential experiment designs for screening and tuning parameters of stochastic heuristics[R/OL].[2016-11-02]. http://www.imada.sdu.dk/~marco/EMAA/Papers/EMAA06-ridge.pdf.
[14] VAN Beers, KLEIJNEN JACK PC. Customized sequential designs for random simulation experiments:Kriging metamodeling and bootstrapping[J]. European Journal of Operation Research, 2008, 186(3):1099-1113.
[15] PARK S, FOWLER J W, MACKULAK G T, et al. D-optimal sequential experiments for generating a simulation-based cycle time-throughput curve[J]. Operations Research, 2002, 50(6):981-990.
[16] GHOSH B K, SEN P K. Handbook of sequential analysis[M]. New York:Marcel Dekker Inc., 1991.
[17] SACKS J, WELCH W J, MITCHELL T J, et al. Design and analysis of computer experiments[J]. Statistical Science, 1989, 4(4):409-423.
[18] WELCH W J, BUCK ITJ, Sacks J. Predicting and computer experiments[J]. Technometrics, 1992, 34(1):15-25.
[19] ANKENMAN B E, NELSON B L, STAUM J. Stochastic kriging for simulation metamodeling[J]. Operations Research, 2010,58(2):371-382. |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|