Adaptive designs of experiments for accurate approximation of a target region

Journal of Mechanical Design

Volumn 132, Issue 7, 2010, Pages 0710081-0710089

  Picheny, Victor ^a   Ginsbourger, David ^b   Roustant, Olivier ^c   Haftka, Raphael T ^d   Kim, Nam Ho ^d  

^a ECOLE CENTRALE PARIS   (France)

^b UNIVERSITY OF BERN   (Switzerland)

^c ECOLE DES MINES DE SAINT ETIENNE   (France)

^d UNIVERSITY OF FLORIDA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINED OPTIMIZATION; ECONOMIC AND SOCIAL EFFECTS; MACHINE DESIGN; MEAN SQUARE ERROR;

% REDUCTIONS; ADAPTIVE DESIGNS; ADAPTIVE STRATEGY; GLOBAL EXPLORATION; GLOBAL UNCERTAINTY; META MODEL; REGION-OF-INTEREST; REGIONS OF INTEREST; TARGET REGIONS; TRADE OFF;

RELIABILITY ANALYSIS;

EID: 77955204195     PISSN: 10500472     EISSN: None     Source Type: Journal    
DOI: 10.1115/1.4001873     Document Type: Article

References (37)

1. Queipo, N., Haftka, R., Shyy, W., Goel, T., Vaidyanathan, R., and Kevin Tucker, P., 2005, "Surrogate-Based Analysis and Optimization," Prog. Aerosp. Sci., 41(1), pp. 1-28.
2. Santner, T., Williams, B., and Notz, W., 2003, The Design and Analysis of Computer Experiments, Springer, New York.
3. Wang, G., and Shan, S., 2007, "Review of Metamodeling Techniques in Support of Engineering Design Optimization," ASME J. Mech. Des., 129, pp. 370-380.
4. Melchers, R., 1987, Structural Reliability: Analysis and Prediction, Ellis Horwood, New York.
5. Rajashekhar, R., and Ellingwood, B., 1993, "A New Look at the Response Surface Approach for Reliability Analysis," Struct. Safety, 12, pp. 205-220.
6. Kuczera, R., and Mourelatos, Z., 2009, "On Estimating the Reliability of Multiple Failure Region Problems Using Approximate Metamodels," ASME J. Mech. Des., 131, p. 121003.
7. Arenbeck, H., Missoum, S., Basudhar, A., and Nikravesh, P., 2010, "Reliability-Based Optimal Design and Tolerancing for Multibody Systems Using Explicit Design Space Decomposition," ASME J. Mech. Des., 132,p. 021010.
8. Ranjan, P., Bingham, D., and Michailidis, G., 2008, "Sequential Experiment Design for Contour Estimation From Complex Computer Codes," Technometrics, 50(4), pp. 527-541.
9. Jones, D., Schonlau, M., and Welch, W., 1998, "Efficient Global Optimization of Expensive Black-Box Functions," J. Global Optim., 13(4), pp. 455-492.
10. Tu, C., and Barton, R., 1997. "Production Yield Estimation by the Metamodel Method With a Boundary-Focused Experiment Design," ASME Design Engineering Technical Conference, American Society of Mechanical Engineers.
11. Vazquez, E., and Bect, J., 2009. "A Sequential Bayesian Algorithm to Estimate a Probability of Failure," Proceedings of 15th IFAC Symposium on System Identification (SYSID), Saint-Malo, France.
12. Matheron, G., 1969. "Le Krigeage Universel," Cahiers du centre de morphologie mathematique, 1.
13. Rasmussen, C., and Williams, C., 2006, Gaussian Processes for Machine Learning, Springer, New York.
14. Martin, J., and Simpson, T., 2004. "A Monte Carlo Simulation of the Kriging Model," Tenth AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, pp. 2004-4483.
15. Oakley, J., and O'Hagan, A., 2004, "Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach," J. R. Stat. Soc. Ser. B (Methodol.), 66, pp. 751-769.
16. McKay, M., Beckman, R., and Conover, W., 2000, "A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code," Technometrics, 42, pp. 55-61.
17. Box, G., and Draper, N., 1986, Empirical Model-Building and Response Surface, Wiley Series in Probability and Mathematical Statistics, Wiley, New York.
18. Kiefer, J., 1961, "Optimum Designs in Regression Problems, II," Ann. Math. Stat., 32, pp. 298-325.
19. St. John, R., and Draper, N., 1975, "D-Optimality for regression Designs: A Review," Technometrics, 17, pp. 15-23.
20. Sacks, J., Schiller, S., and Welch, W., 1989, "Designs for Computer Experiments," Technometrics, 31, pp. 41-47.
21. Lin, Y., Luo, D., Bailey, T., Khire, R., Wang, J., and Simpson, T. W., 2008, "Model Validation and Error Modeling to Support Sequential Sampling," ASME Paper No. DETC2008/DAC-49336.
22. Turner, C., Campbell, M., and Crawford, R., 2003, "Generic Sequential Sampling for Meta-Model Approximations," ASME 2003 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, pp. 2-6.
23. Williams, B., Santner, T., and Notz, W., 2000, "Sequential Design of Computer Experiments to Minimize Integrated Response Functions," Stat. Sin., 10(4), pp. 1133-1152.
24. Currin, C., Mitchell, T., Morris, M., and Ylvisaker, D., 1991, "Bayesian Prediction of Deterministic Functions, With Applications to the Design and Analysis of Computer Experiments," J. Am. Stat. Assoc., 86, pp. 953-963.
25. Osio, I., and Amon, C., 1996, "An Engineering Design Methodology With Multistage Bayesian Surrogates and Optimal Sampling," Res. Eng. Des., 8(4), pp. 189-206.
26. Jin, R., Chen, W., and Sudjianto, A., 2002, "On Sequential Sampling for Global Metamodeling in Engineering Design," Proceedings of DETC, Vol. 2, Citeseer.
27. Jones, D., 2001, "A Taxonomy of Global Optimization Methods Based on Response Surfaces," J. Global Optim., 21(4), pp. 345-383.
28. Shan, S., and Wang, G., 2004, "Space Exploration and Global Optimization for Computationally Intensive Design Problems: A Rough Set Based Approach," Struct. Multidiscip. Optim., 28(6), pp. 427-441.
29. Oakley, J., 2004, "Estimating Percentiles of Uncertain Computer Code Outputs," Appl. Stat., 53, pp. 83-93.
30. Haldar, A., and Mahadevan, S., 2000, Probability, Reliability and Statistical Methods in Engineering Design, Wiley, New York.
31. Gano, S., Renaud, J., Martin, J., and Simpson, T., 2006, "Update Strategies for Kriging Models Used in Variable Fidelity Optimization," Struct. Multidiscip. Optim., 32(4), pp. 287-298.
32. Ginsbourger, D., 2009, "Metamodeles Multiples Pour L'approximation et L'optimisation de Fonctions Numeriques Multivariables," Ph.D. thesis, Ecole Nationale Superieure des Mines de Saint Etienne.
33. Zhang, F., 2005, The Schur Complement and Its Applications, Springer Verlag, New York.
34. Neal, R., 1997, "Monte Carlo Implementation of Gaussian Process Models for Bayesian Regression and Classification," Arxiv preprint physics/9701026.
35. Hansen, N., and Kern, S., 2004, "Evaluating the CMA Evolution Strategy on Multimodal Test Functions," Lect. Notes Comput. Sci., 3242, pp. 282-291.
36. Chipperfield, A., Fleming, P., Pohlheim, H., and Fonseca, C., 1994, "Genetic Algorithm Toolbox Users Guide," ACSE Research Report No. 512.
37. Sobol, I., 1976, "Uniformly Distributed Sequences With an Additional Uniform Property," Zh. Vychisl. Mat. Mat. Fiz, 16, pp. 1332-1337.