Journal ArticleDOI
Metamodeling in Multidisciplinary Design Optimization: How Far Have We Really Come?
TLDR
The extent to which the use of metamodeling techniques inmultidisciplinary design optimization have evolved in the 25 years since the seminal paper on design and analysis of computer experiments is addressed.Abstract:
The use of metamodeling techniques in the design and analysis of computer experiments has progressed remarkably in the past 25 years, but how far has the field really come? This is the question addressed in this paper, namely, the extent to which the use of metamodeling techniques in multidisciplinary design optimization have evolved in the 25 years since the seminal paper on design and analysis of computer experiments by Sacks et al. (“Design and Analysis of Computer Experiments,” Statistical Science, Vol. 4, No. 4, 1989, pp. 409–435). Rather than a technical review of the entire body of metamodeling literature, the focus is on the evolution and motivation for advancements in metamodeling with some discussion on the research itself; not surprisingly, much of the current research motivation is the same as it was in the past. Based on current research thrusts in the field, multifidelity approximations and ensembles (i.e., sets) of metamodels, as well as the availability of metamodels within commercial soft...read more
Citations
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Journal ArticleDOI
On design optimization for structural crashworthiness and its state of the art
TL;DR: A comprehensive review of the important studies on design optimization for structural crashworthiness and energy absorption is provided in this article, where the authors provide some conclusions and recommendations to enable academia and industry to become more aware of the available capabilities and recent developments in design optimization.
Journal ArticleDOI
A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design
TL;DR: This article categorizes, reviews, and analyzes the state-of-the-art single−/multi-response adaptive sampling approaches for global metamodeling in support of simulation-based engineering design and discusses some important issues that affect the success of an adaptive sampling approach.
Journal ArticleDOI
Review of multi-fidelity models
TL;DR: It is found that time savings are highly problem dependent and that MFM methods provided time savings up to 90% and guidelines for authors to present their MFM savings in a way that is useful to future MFM users are included.
Journal ArticleDOI
A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses
TL;DR: A comprehensive and state-of-the art survey on common surrogate modeling techniques and surrogate-based optimization methods is given, with an emphasis on models selection and validation, dimensionality reduction, sensitivity analyses, constraints handling or infill and stopping criteria.
References
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A study of cross-validation and bootstrap for accuracy estimation and model selection
TL;DR: The results indicate that for real-word datasets similar to the authors', the best method to use for model selection is ten fold stratified cross validation even if computation power allows using more folds.
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A tutorial on support vector regression
TL;DR: This tutorial gives an overview of the basic ideas underlying Support Vector (SV) machines for function estimation, and includes a summary of currently used algorithms for training SV machines, covering both the quadratic programming part and advanced methods for dealing with large datasets.
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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.
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Statistics for spatial data
Noel A Cressie,Noel A Cressie +1 more
TL;DR: In this paper, the authors present a survey of statistics for spatial data in the field of geostatistics, including spatial point patterns and point patterns modeling objects, using Lattice Data and spatial models on lattices.
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.