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TECHNICAL PAPERS

Bayesian Surrogates Applied to Conceptual Stages of the Engineering Design Process

[+] Author and Article Information
Jorge E. Pacheco

Institute for Complex Engineered Systems, Carnegie Mellon University, Pittsburgh, PA 15213e-mail: jpacheco@andrew.cmu.edu

Cristina H. Amon

Mechanical Engineering and Institute for Complex Engineered Systems, Carnegie Mellon University, Pittsburgh, PA 15213e-mail: camon@cmu.edu

Susan Finger

Civil & Environmental Engineering and Institute for Complex Engineered Systems, Carnegie Mellon University, Pittsburgh, PA 15213e-mail: sfinger@ri.cmu.edu

J. Mech. Des 125(4), 664-672 (Jan 22, 2004) (9 pages) doi:10.1115/1.1631580 History: Received November 01, 2001; Revised May 01, 2003; Online January 22, 2004
Copyright © 2003 by ASME
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References

Kleijnen, J. P., 1987, Statistical Tools for Simulation Practitioners, Marcel Dekker.
Lu, S., Bukkapatnam, S., Ge, P., and Wang, N., 1999, “Backward Mapping Methodology for Design Synthesis,” DTM 8766, ASME Design Engineering Technical Conferences, Las Vegas, Nevada, pp. 1–11.
Osio,  I. G., and Amon,  C. H., 1996, “An Engineering Design Methodology With Multistage Bayesian Surrogates and Optimal Sampling,” Res. Eng. Des., 8(4), pp. 189–206.
Krishnamurty, S., and Doraiswamy, S., 2000, “Bayesian Analysis in Engineering Model Assessment,” DTM 14546, ASME Design Engineering Technical Conferences, Baltimore, MD.
Shewry,  M., and Wynn,  H., 1987, “Maximum Entropy Sampling,” Journal of Applied Statistics,14(2), pp. 165–170.
Sacks,  J., Welch,  W. J., Mitchell,  T. J., and Wynn,  H. P., 1989, “Design and Analysis of Computer Experiments,” Stat. Sci., 4(4), pp. 409–435.
Cressie, N., 1991, Statistics for Spatial Data, John Wiley and Sons.
Matheron,  G., 1963, “Principles of Geostatistics,” Econ. Geol., 58, pp. 1246–1266.
Krige,  D. G., 1951, “A Statistical Approach to Some Basic Mine Valuation Problems on the Witwatersrand,” Journal of the South African Institute of Mining and Metallurgy,52, pp. 119–139, Reprinted 1994.
Otto, J. C., Paraschivoiu, M., Yesilyurt, S., and Patera, A., 1995, “Bayesian-Validated Computer Simulation Surrogates for Optimization and Design,” ICASE Workshop on Multidisciplinary Design Optimization, Hampton, VA.
Yesilyurt,  S., Ghaddar,  C. K., Cruz,  M. E., and Patera,  A. T., 1996, “Bayesian-validated Surrogates for Noisy Computer Simulations; Application to Random Media,” SIAM J. Sci. Comput. (USA), 17(4), pp. 973–992.
Osio, I. G., 1996, Multistage Bayesian Surrogates and Optimal Sampling for Engineering Design and Process Improvement, Carnegie Mellon University, Pittsburgh, PA.
Leoni, N., 1999, Integrating Information Sources into Global Models: A Surrogate Methodology for Product and Process Development, Carnegie Mellon University, Pittsburgh, PA.
Leoni,  N., and Amon,  C. H., 2000, “Bayesian Surrogates for Integrating Numerical, Analytical, and Experimental Data: Application to Inverse Heat Transfer in Wearable Computers,” IEEE Trans. Compon., Packag. Manuf. Technol., Part A, 23(1), pp. 23–32.
Hertz, J., Krogh, A., and Palmer, R., 1991, Introduction to the Theory of Neural Computation, Addison Wesley.
Dyn,  N., Levin,  D., and Rippa,  S., 1986, “Numerical Procedures for Surface Fitting of Scattered Data by Radial Functions,” SIAM J. Sci. Comput. (USA), 7(2), pp. 639–659.
Box, G., and Draper, N. R., 1987, Empirical Model-Building and Response Surfaces, John Wiley and Sons.
Jin,  R., Chen,  W., and Simpson,  T. W., 2001, “Comparative Studies of Metamodeling Techniques under Multiple Modeling Criteria,” Struct. Optim., 23(1), pp. 1–13.
Simpson,  T. W., Peplinski,  J. D., Koch,  P. N., and Allen,  J. K., 2001, “Metamodels for Computer-Based Engineering Design: Survey and Recommendations,” Eng. Comput., 17(2), pp. 129–150.
Pacheco, J. E., 2003, A Methodology for Surrogate Model Building in the Engineering Design Process, Carnegie Mellon University, Pittsburgh, PA.
Akaike,  H., 1974, “A New Look at the Statistical Model Identification,” IEEE Trans. Autom. Control, 6, pp. 716–23.
Mitchell,  T. J., and Morris,  M. D., 1992, “Bayesian Design and Analysis of Computer Experiments—2 Examples,” Statistica Sinica,2(2), pp. 359–379.
Incropera, F. P., and DeWitt, D. P., 1996, Fundamentals of Heat and Mass Transfer, John Wiley and Sons.
Owen,  A. B., 1992, “Orthogonal Arrays for Computer Experiments, Integration and Visualization,” Statistica Sinica,2(2), pp. 439–452.

Figures

Grahic Jump Location
Plot of 1st and 2nd stage surrogates for analytical test function f(t)=Cos[8(t−0.3)]+3(t−0.2)+Sin[1/(t+0.2)+2], built from a) constant variance framework and b) covariance-based framework
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Two-stage surrogate and implicit bounds for analytical test function f(t)=Cos[8(t−0.3)]+3(t−0.2)+Sin[1/(t+0.2)+2] using covariance-based framework with implicit bounds
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One dimensional analytical test function in the t:[0,1] domain
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Circular pipe with outside insulation in the presence of a convective flow
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Heat transfer (q) versus the external radius (ro) and the convective heat transfer coefficient (h)
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Sampling points for heat transfer system with an analytical solution
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Third stage surrogate model using implicit bounds for heat transfer (q) versus the external radius (ro) and the convective heat transfer coefficient (h)
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Thermal design problem for a support structure that maximizes heat transfer
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Sampling points of numerical simulations for design problem
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Heat transfer (q) versus non-dimensional length and height of the plastic support for fourth stage surrogate

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