scispace - formally typeset
Journal ArticleDOI

Review of Metamodeling Techniques in Support of Engineering Design Optimization

Gongming Wang, +1 more
- Vol. 129, Iss: 4, pp 370-380
Reads0
Chats0
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

read more

Citations
More filters
Proceedings ArticleDOI

Application of surrogate modeling to generate compact and PVT-sensitive IBIS models

TL;DR: A new proposal of applying surrogate-modeling in Input-output Buffer Information Specification (IBIS) saves the IBIS data storage resource, extends the model utility to various process-voltage-temperature (PVT) simulations and eliminates the data interpolation deviations.
Journal ArticleDOI

An Adaptive Aggregation-Based Approach for Expensively Constrained Black-Box Optimization Problems

TL;DR: The situational adaptive Kreisselmeier and Steinhauser (SAKS) method was employed in the development of a hybrid adaptive aggregation-based constraint handling strategy for expensive black-box constraint functions.
Journal ArticleDOI

Multiobjective constraints for climate model parameter choices: Pragmatic Pareto fronts in CESM1

TL;DR: In this paper, a multi-objective optimization approach is used to investigate parameter sensitivity and optimization in the face of trade-offs in high-dimensional input-output systems, where model output is a function of many variables.
Journal ArticleDOI

SGOP: Surrogate-assisted global optimization using a Pareto-based sampling strategy

TL;DR: A Pareto-based multi-point sampling strategy is presented to improve iterative efficiency and SGOP is used for the shape optimization of a blended-wing-body underwater glider and the lift–drag-ratio gets remarkable improvement.
Journal ArticleDOI

Modelling of a hydrokinetic energy converter for flow-induced vibration based on experimental data

TL;DR: In this paper, the harnessed power and efficiency of the VIVACE Converter were modeled based on a surrogate model methodology, in vortex-induced vibration (VIV) and galloping region.
References
More filters
Book

Response Surface Methodology: Process and Product Optimization Using Designed Experiments

TL;DR: Using a practical approach, this book discusses two-level factorial and fractional factorial designs, several aspects of empirical modeling with regression techniques, focusing on response surface methodology, mixture experiments and robust design techniques.
Journal ArticleDOI

A comparison of three methods for selecting values of input variables in the analysis of output from a computer code

TL;DR: In this paper, two sampling plans are examined as alternatives to simple random sampling in Monte Carlo studies and they are shown to be improvements over simple sampling with respect to variance for a class of estimators which includes the sample mean and the empirical distribution function.
Journal ArticleDOI

Efficient Global Optimization of Expensive Black-Box Functions

TL;DR: This paper introduces the reader to a response surface methodology that is especially good at modeling the nonlinear, multimodal functions that often occur in engineering and shows how these approximating functions can be used to construct an efficient global optimization algorithm with a credible stopping rule.
Journal ArticleDOI

Multivariate Adaptive Regression Splines

TL;DR: In this article, a new method is presented for flexible regression modeling of high dimensional data, which takes the form of an expansion in product spline basis functions, where the number of basis functions as well as the parameters associated with each one (product degree and knot locations) are automatically determined by the data.
Journal ArticleDOI

The design and analysis of computer experiments

TL;DR: This paper presents a meta-modelling framework for estimating Output from Computer Experiments-Predicting Output from Training Data and Criteria Based Designs for computer Experiments.
Related Papers (5)