Review of Metamodeling Techniques in Support of Engineering Design Optimization

[+] Author and Article Information
G. Gary Wang1

Department of Mechanical and Manufacturing Engineering, The University of Manitoba, Winnipeg, MB, R3T 5V6, Canadagary_wang@umanitoba.ca

S. Shan

Department of Mechanical and Manufacturing Engineering, The University of Manitoba, Winnipeg, MB, R3T 5V6, Canada


Corresponding author.

J. Mech. Des 129(4), 370-380 (May 04, 2006) (11 pages) doi:10.1115/1.2429697 History: Received July 07, 2005; Revised May 04, 2006

Computation-intensive design problems are becoming increasingly common in manufacturing industries. The computation burden is often caused by expensive analysis and simulation processes in order to reach a comparable level of accuracy as physical testing data. To address such a challenge, approximation or metamodeling techniques are often used. Metamodeling techniques have been developed from many different disciplines including statistics, mathematics, computer science, and various engineering disciplines. These metamodels are initially developed as “surrogates” of the expensive simulation process in order to improve the overall computation efficiency. They are then found to be a valuable tool to support a wide scope of activities in modern engineering design, especially design optimization. This work reviews the state-of-the-art metamodel-based techniques from a practitioner’s perspective according to the role of metamodeling in supporting design optimization, including model approximation, design space exploration, problem formulation, and solving various types of optimization problems. Challenges and future development of metamodeling in support of engineering design is also analyzed and discussed.

Copyright © 2007 by American Society of Mechanical Engineers
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Figure 1

Metamodeling and its role in support of engineering design optimization

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Figure 2

MBDO strategies: (a) sequential approach; (b) adaptive MBDO; and (c) direct sampling approach

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Figure 3

Schematic of engine cooling bay inlet flow (144)

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Figure 4

A typical HSCT configuration (147)




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