全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于概率分布距离的多响应模型确认度量

DOI: 10.13195/j.kzyjc.2014.0361, PP. 1014-1020

Keywords: 模型确认,概率分布距离,置信区间,多响应确认度量

Full-Text   Cite this paper   Add to My Lib

Abstract:

针对模型确认中的确认度量问题,构造实验观测数据经验概率分布的置信包络.通过计算其与模型响应概率分布之间距离的上/下确界,给出基于概率分布距离确认度量的置信区间.通过构造与实验观测数据有关的协方差矩阵,给出基于概率分布距离的多响应模型确认度量及其置信区间的求解方式.该度量利用了模型输出与实验观测的完整概率分布信息,并且考虑了各模型响应间的相关性.算例仿真结果表明其确认错误率低于现有的其他两种确认度量.

References

[1]  Trucano T G, Swiler L P, Igusa T, et al. Calibration, vali-dation, and sensitivity analysis: What’s what[J]. Reliability Engineering and System Safety, 2006, 91(10/11): 1331-1357.
[2]  Box G E, Draper N R. Empirical model-building and response surfaces[M]. Minnesota: John Wiley Ltd, 1987: 424.
[3]  Trucano T G, Easterling R G, Dowding K L, et al. Description of the Sandia validation metrics project[R]. Albuquerque: Sandia National Laboratories, 2001.
[4]  Oberkampf W L, Trucano T G. Verification and validation benchmarks[R]. Albuquerque: Sandia National Laborato-ries, 2007.
[5]  Roy C J, Oberkampf W L. A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing[J]. Computer Methods in Applied Mechanics and Engineering, 2011, 200(25-28): 2131-2144.
[6]  Liu Y, ChenW, Arendt P, et al. Toward a better understand-ing of model validation metrics[J]. J of Mechanical Design, 2011, 133(7): 48-60.
[7]  Hills R G, Trucano T G. Statistical validation of engineer-ing and scientific models: Background[R]. Albuquerque: Sandia National Laboratories, 1999.
[8]  Hills R G, Trucano T G. Statistical validation of engineer-ing and scientific models: A maximum likelihood based metric[R]. Albuquerque: Sandia National Laboratories, 2002.
[9]  Buranathiti T, Cao J, Chen W, et al. Approaches for model validation: Methodology and illustration on a sheet metal flanging process[J]. J of Manufacturing Science and Engineering, 2006, 128(2): 588-597.
[10]  Rebba R, Mahadevan S. Validation of models with multivariate output[J]. Reliability Engineering and System Safety, 2006, 91(8): 861-871.
[11]  Rebba R, Mahadevan S. Computational methods for model reliability assessment[J]. Reliability Engineering and System Safety, 2008, 93(8): 1197-1207.
[12]  Oberkampf W L, Trucano T G, Hirsch C. Verification, validation, and predictive capability in computational engineering and physics[J]. Applied Mechanics Reviews, 2004, 57(3): 345-384.
[13]  Oberkampf W L, Barone M F. Measures of agreement be-tween computation and experiment: Validation metrics[J]. J of Computational Physics, 2006, 217(1): 5-36.
[14]  Ferson S, Oberkampf W L, Ginzburg L. Model valida-tion and predictive capability for the thermal challenge problem[J]. Computer Methods in Applied Mechanics and Engineering, 2008, 197(29-32): 2408-2430.
[15]  Miller L H. Table of percentage points of Kolmogorovstatistics[J]. J of the American Statistical Association, 1956, 51(273): 111-121.
[16]  Dowding K J, Pilch M, Hills R G. Formulation of the thermal problem[J]. Computer Methods in Applied Mechanics and Engineering, 2008, 197(29-32): 2385-2389.
[17]  张保强, 陈国平, 郭勤涛. 模型确认热传导挑战问题求解的贝叶斯方法[J]. 航空学报, 2011, 32(7): 1202-1209.
[18]  (Zhang B Q, Chen G P, Guo Q T. Solution of model validation thermal challenge problem using a Bayesian method[J]. Acta Aeronautica et Astronautica Sinica, 2011, 32(7): 1202-1209.)
[19]  McFarland J, Mahadevan S. Multivariate significance test-ing and model calibration under uncertainty[J]. Computer Methods in Applied Mechanics and Engineering, 2008, 197(29-32): 2467-2479.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133