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Journal ArticleDOI

Review of Metamodeling Techniques in Support of Engineering Design Optimization

Gongming Wang, +1 more
- Vol. 129, Iss: 4, pp 370-380
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TLDR
This work reviews the state-of-the-art metamodel-based techniques from a practitioner's perspective according to the role of meetamodeling in supporting design optimization, including model approximation, design space exploration, problem formulation, and solving various types of optimization problems.
Abstract
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 © 2006 by ASME

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Citations
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Journal ArticleDOI

Robust Tolerance Optimization for Internal Combustion Engines Under Parameter and Model Uncertainties Considering Metamodeling Uncertainty From Gaussian Processes

TL;DR: The proposed RO approach provides a general and systematic procedure for determining robust optimal tolerances and has competitive advantages over traditional experience-based tolerance design.
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Multicriteria shape design of an aerosol can

TL;DR: A coupling between the Normal Boundary Intersection – NBI – algorithm with Radial Basis Function – RBF – metamodel is performed in order to have a simple tool with a reasonable calculation time to solve multicriteria optimization problems.
Journal ArticleDOI

Development of artificial neural network based metamodels for inactivation of anthrax spores in ventilated spaces using computational fluid dynamics.

TL;DR: Linear, quadratic, and artificial neural network (ANN)-based metamodels were developed for predicting the extent of anthrax spore inactivation by chlorine dioxide in a ventilated three-dimensional space over time from computational fluid dynamics model (CFD) simulation data.
Journal ArticleDOI

Metamodelling Techniques for the Optimal Design of Low-Noise Amplifiers

TL;DR: This article deals with the optimal sizing of low-noise amplifiers (LNAs) using newly proposed metamodeling techniques and comparisons between results obtained and those of the simulation are presented to show the perfect agreement.
Proceedings ArticleDOI

Enabling high-dimensional surrogate-assisted optimization by using sliding windows

TL;DR: A possible meta-algorithm scheme for the application of surrogate models to high-dimensional optimization problems and the main assumption is that for some of these expensive problems the nonlinear interactions between variables are sparse.
References
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