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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

Figures

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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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