Analytical variance-based global sensitivity analysis in simulation-based design under uncertainty

Journal of Mechanical Design

Volumn 127, Issue 5, 2005, Pages 875-886

  Chen, Wei ^a   Jin, Ruichen ^b   Sudjianto, Agus ^c  

^a Northwestern University   (United States)

^b FORD MOTOR COMPANY   (United States)

^c Bank of America Corp   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; MATHEMATICAL MODELS; PROBABILITY; SENSITIVITY ANALYSIS; STATISTICAL METHODS;

GLOBAL SENSITIVITY ANALYSIS; PROBABILISTIC VARIATION; SIMULATION BASED DESIGN;

MACHINE DESIGN;

EID: 24344462705     PISSN: 10500472     EISSN: None     Source Type: Journal    
DOI: 10.1115/1.1904642     Document Type: Article

References (31)

1. Manring, N. D., 2003, "Sensitivity Analysis of the Conical-Shaped Equivalent Model of a Bolted Joint," ASME J. Mech. Des., 125, 642-646.
2. Du, X., and Chen, W., 2004, "Sequential Optimization and Reliability Assessment Method for Efficient Probabilistic Design," ASME J. Mech. Des., 126(2), pp. 225-233.
3. Du, X., Sodjianto, A., and Chen, W., 2004, "An Integrated Framework for Optimization under Uncertainty using Inverse Reliability Strategy," ASME J. Mech. Des., 126(4), 562-570.
4. Youn, B. D., and Choi, K. K., 2004, "An Investigation of Nonlinearity of Reliability-Based Design Optimization Approaches," ASME J. Mech. Des., 126, 403-411.
5. Nikolaidis, E., Chen, S., Codney, H., Haftka, R. T., and Rosca, R., 2004, "Comparison of Probability and Possibility for Design Against Catastrophic Failure under Uncertainty," ASME J. Mech. Des., 126, 386-394.
6. Liu, H., Chen, W., and Sudjianto, A., 2004, "Relative Entropy Based Method for Global and Regional Sensitivity Analysis in Probabilistic Design," DETC2004-57500, 2004 ASME Design Automation Conference, Salt Lake City, UT, September 28-October 2, 2004.
7. Box, G. E. P., Hunter, W. G., and Hunter, J. S., 1978, Statistics for Experimenters, Wiley, New York.
8. Saltalli, A., Tarantola, S., and Chan, K., 1999, "A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output," Technometrics, 41(1), 39-56.
9. McKay, M. D., Morrison, J. D., and Upton, S. C., (1999), "Evaluating prediction uncertainty in simulation models," Comput. Phys. Commun., 117, pp. 44-51.
10. Homma, T., and Saltelli, A., 1996, "Importance Measures in Global Sensitivity Analysis of Nonlinear Models," Reliability Eng. Sys. Safety, 52, pp. 1-17.
11. Sobol, I. M., 1993, "Sensitivity Analysis for Nonlinear Mathematical Models," Mat. Model., 1, 407-414 [translation of Sobol', 1990, "Sensitivity Estimates for Nonlinear Mathematical Models," Matematicheskoe Modelirovanie, 2, 112-118 (in Russian).
12. Reedijk, C. I., 2000, "Sensitivity Analysis of Model Output: Performance of various local and global sensitivity measures on reliability problems," Master's Thesis, Delft University of Technology, 2000.
13. Helton, J. C.. 1993, "Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal," Reliability Eng. Sys. Safety, 42, 327-367.
14. Chan, K., Saltelli, A., Tarantola, S., 1997, "Sensitivity Analysis of Model Output: Variance-Based Methods Make the Difference," Proceedings of the 1997 Winter Simulation Conference.
15. Chen, W., Allen, J. K., Schrage, D. P., and Mistree, F., 1997, "Statistical Experimentation Methods for Achieving Affordable Concurrent Design," AIAA J., 35(5), 893-900.
16. Hardy, R. L., 1971, "Multiquadratic equations of topography and other irregular surfaces," J. Geophys. Res., 76, pp. 1905-1915.
17. Dyn, N., Levin, D., and Rippa, S., 1986, "Numerical procedures for surface fitting of scattered data by radial basis functions," SIAM (Sac. Ind. Appl. Math.) J. Sci. Stat. Comput., 7(2), pp. 639-659.
18. Sacks, J., Welch, W. J., Mitchell, T. J., and Wynn, H. P., 1989, "Design and Analysis of Computer Experiments," Stat. Sci., 4, No. 4, pp. 409-435.
19. Currin, C., Mitchell, T., Morris, M. D., and Ylvisaker, D., 1991, "Bayesian prediction of deterministic functions, with applications to the design and analysis of computer experiments," J. Am. Stat. Assoc., 86 (416), 953-963.
20. Owen, A. B., 1999, "Monte Carlo quasi-Monte Carlo and Randomized quasi-Monte Carlo," in H. Niederreiter and J. Spanier, eds., Monte Carlo and quasi-Monte Carlo Methods, pp. 86-97.
21. Friedman, J. H., 1991, "Multivariate Adaptive Regression Splines," Ann. Stat., 19(1), pp. 1-141.
22. Jin, R., 2004, "Enhancements of Metamodeling Techniques in Engineering Design," PhD dissertation, University of Illinois at Chicago, Chicago, IL.
23. Phadke, M. S., 1989, Quality Engineering Using Robust Design, Prentice Hall, Englewood Cliffs, NJ.
24. Hastie, T., Tibshirani, R., Friedman, J., 2001, The Elements of Statistical Learning: data mining, inference, and prediction, Springer-Verlag, New York.
25. Mohamedshah, Y., Council, F., 1997, "Synthesis of Rollover Research," March 10, 1997.
26. Chen, W., Garimella, R., and Michelena, N., 2001, "Robust Design for Improved Vehicle Handling Under a Range of Maneuver Conditions," Eng. Optimiz., 33, No 3, 303-326.
27. Sayers, M. W., and Riley, S. M., 1996, "Modeling Assumptions for Realistic Multibody Simulations of the Yaw and Roll Behavior of Heavy Trucks," SAE Paper No. 960173. Society of Automotive Engineers, Warrendale, PA.
28. Michelena, N., and Kim, H.-M., 1998, "Worst-Case Design for Vehicle Handling," Fourth Annual Conference on Modeling and Simulation of Ground Vehicles, The Automotive Research Center, The University of Michigan, Ann Arbor, May 19-20, 1998.
29. Jin, R., Chen, W., and Sudjianto, A., "An Efficient Algorithm for Constructing Optimal Design of Computer Experiments," DETC-DAC48760, 2003 ASME Design Automation Conference, Chicago, IL, September 2-6, 2003, to appear in Journal of Statistical Planning and Inference.
30. Jin, R., Chen, W., and Simpson, T., 2001, "Comparative Studies of Metamodeling Techniques under Multiple Modeling Criteria," Journal of Structural & Multidisciplinary Optimization, 23(1), pp. 1-13.
31. Chen, W., Jin, R., and Sudjianto, A., 2004, "Analytical Uncertainty Propagation in Simulation-Based Design under Uncertainty," AIAA-2004-4356, 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Albany, NY, August 30-September 1, 2004.