Engineering Design via Surrogate Modelling: A Practical Guide

Front Cover
John Wiley & Sons, Sep 15, 2008 - Technology & Engineering - 240 pages
Surrogate models expedite the search for promising designs by standing in for expensive design evaluations or simulations. They provide a global model of some metric of a design (such as weight, aerodynamic drag, cost, etc.), which can then be optimized efficiently.

Engineering Design via Surrogate Modelling is a self-contained guide to surrogate models and their use in engineering design. The fundamentals of building, selecting, validating, searching and refining a surrogate are presented in a manner accessible to novices in the field. Figures are used liberally to explain the key concepts and clearly show the differences between the various techniques, as well as to emphasize the intuitive nature of the conceptual and mathematical reasoning behind them.

More advanced and recent concepts are each presented in stand-alone chapters, allowing the reader to concentrate on material pertinent to their current design problem, and concepts are clearly demonstrated using simple design problems. This collection of advanced concepts (visualization, constraint handling, coping with noisy data, gradient-enhanced modelling, multi-fidelity analysis and multiple objectives) represents an invaluable reference manual for engineers and researchers active in the area.

Engineering Design via Surrogate Modelling is complemented by a suite of Matlab codes, allowing the reader to apply all the techniques presented to their own design problems. By applying statistical modelling to engineering design, this book bridges the wide gap between the engineering and statistics communities. It will appeal to postgraduates and researchers across the academic engineering design community as well as practising design engineers.

  • Provides an inclusive and practical guide to using surrogates in engineering design.
  • Presents the fundamentals of building, selecting, validating, searching and refining a surrogate model.
  • Guides the reader through the practical implementation of a surrogate-based design process using a set of case studies from real engineering design challenges.

Accompanied by a companion website featuring Matlab software at http://www.wiley.com/go/forrester

 

Selected pages

Contents

1 Sampling Plans
3
2 Constructing a Surrogate
33
3 Exploring and Exploiting a Surrogate
77
Part II Advanced Concepts
109
4 Visualization
111
5 Constraints
117
6 Infill Criteria with Noisy Data
141
7 Exploiting Gradient Information
155
8 Multifidelity Analysis
167
9 Multiple Design Objectives
179
Appendix Example Problems
195
Index
205
Color Plates
213
Copyright

Other editions - View all

Engineering Design Via Surrogate Modelling: A Practical Guide
Alexander Forrester,András Sóbester,Andy Keane
Snippet view - 2008
Engineering Design via Surrogate Modelling: A Practical Guide
Alexander Forrester,Dr. Andras Sobester,Andy Keane
No preview available - 2008

Common terms and phrases

50 Maximin rank aerofoil approach approximation based infill calculate cheap Cholesky factorization co-Kriging colour version computer experiments conditional likelihood consider constrained expected improvement constraint boundary constraint function contours criterion cross-validation design space design variables elementary effects end end Engineering Design Equation evaluation example expensive feasible Forrester Gaussian process genetic algorithm global ModelInfo global optimum goal seeking gradient imputed infeasible infill criteria infill points infill strategy Inputs interpolating Keane Kriging model Kriging prediction Latin hypercube Latin hypercube sampling level curve ln-likelihood lower bound MATLAB maximizing maximum method minimize minimum model parameters noise objective function observed data one-variable optimization Outputs Pareto front Pareto set penalty Plate plot polynomial prediction in Figure predictor problem radial basis function random region RMSE sample data sample points sampling plan shown in Figure simulation Sóbester space-filling subset support vectors surrogate model test function true function update zero

About the author (2008)

Dr. Alexander I. J. Forrester is Lecturer in Engineering Design at the University of Southampton. His main area of research focuses on improving the efficiency with which expensive analysis (particularly computational fluid dynamics) is used in design. His techniques have been applied to wing aerodynamics, satellite structures, sports equipment design and Formula One.

Dr Andras Sobester is a Lecturer and EPSRC/ Royal Academy of Engineering research Fellow in the School of Engineering Sciences at the University of Southampton. His research interests include aircraft design, aerodynamic shape parameterization and optimization, as well as engineering design technology in general.

Professor Andy J. Keane currently holds the Chair of Computational Engineering at the University of Southampton. He leads the University's Computational Engineering at the Design Research Group and directs the rolls-Royce University Technology centre for Computational Engineering. His interests lie primarily in the aerospace sciences, with a focus on the design of aerospace systems using computational methods. He has published over two hundred papers and three books in this area, many of which deal with surrogate modelling concepts.

Bibliographic information

TitleEngineering Design via Surrogate Modelling: A Practical Guide
AuthorsAlexander Forrester, András Sóbester, Andy Keane
PublisherJohn Wiley & Sons, 2008
ISBN0470770791, 9780470770795
Length240 pages
Subjects › 

Technology & Engineering / Drafting & Mechanical Drawing
Technology & Engineering / Manufacturing
Technology & Engineering / Mechanical
  
Export CitationBiBTeX EndNote RefMan