Jaroslaw Sobieszczanski-Sobieski, Alan Morris, Michel van Tooren

Multidisciplinary Design Optimization Supported by Knowledge Based Engineering

• Gebundenes Buch

Produktbeschreibung

Multidisciplinary Design Optimization supported by Knowledge Based Engineering supports engineers confronting this daunting and new design paradigm. It describes methodology for conducting a system design in a systematic and rigorous manner that supports human creativity to optimize the design objective(s) subject to constraints and uncertainties. The material presented builds on decades of experience in Multidisciplinary Design Optimization (MDO) methods, progress in concurrent computing, and Knowledge Based Engineering (KBE) tools.

Key features:
* Comprehensively covers MDO and is the only book to directly link this with KBE methods
* Provides a pathway through basic optimization methods to MDO methods
* Directly links design optimization methods to the massively concurrent computing technology
* Emphasizes real world engineering design practice in the application of optimization methods

Multidisciplinary Design Optimization supported by Knowledge Based Engineering is a one-stop-shop guide to the state-of-the-art tools in the MDO and KBE disciplines for systems design engineers and managers. Graduate or post-graduate students can use it to support their design courses, and researchers or developers of computer-aided design methods will find it useful as a wide-ranging reference.

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Produktdetails

• Verlag: Wiley & Sons
• 1. Auflage
• Seitenzahl: 400
• Erscheinungstermin: 28. September 2015
• Englisch
• Abmessung: 246mm x 173mm x 23mm
• Gewicht: 794g
• ISBN-13: 9781118492123
• ISBN-10: 1118492129
• Artikelnr.: 42200662

Autorenporträt

Jaroslaw Sobieszczanski-Sobieski NASA Langley Research Center, USA Alan Morris Cranfield University, UK Michel van Tooren University of South Carolina, USA

Inhaltsangabe

Preface

Acknowledgements

Styles for Equations

Chapter 1 Introduction

Chapter 2 Modern Design and Optimization

Chapter 3 Constrained design space search

Chapter 4 Direct Search Methods for Locating the Optimum of a Design Problem with a Single Objective Function

Chapter 5 Guided Random Search and Network Techniques

Chapter 6 Optimizing Multiple Objective Function Problems

Chapter 7 Sensitivity Analysis

Chapter 8 Multi-Disciplinary Design and Optimization Architectures

Chapter 9 Knowledge Based Engineering, KBE

Chapter 10 Uncertainty-Based Multidisciplinary Design Optimization

Chapter 11 Ways and Means for Control and Reduction of the Optimization Computational Cost and Elapsed Time

Appendix A Implementation of KBE in an MDO System

Appendix B Guide to Implementing an MDO System