Finite Elements-based Optimization: Electromagnetic Product Design and Nondestructive Evaluation [Hardback]

(Electrical and Computer Engineering Department, Michigan State University, East Lansing, USA), (ECE, University of Illinois at Urbana Champaign)
  • Formāts: Hardback, 306 pages, height x width: 235x156 mm, weight: 680 g, 164 Line drawings, black and white; 1 Halftones, black and white; 29 Tables, black and white; 165 Illustrations, black and white
  • Izdošanas datums: 31-Jul-2019
  • Izdevniecība: Productivity Press
  • ISBN-10: 1498759467
  • ISBN-13: 9781498759465
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  • Hardback
  • Cena: 197,05 EUR
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  • Formāts: Hardback, 306 pages, height x width: 235x156 mm, weight: 680 g, 164 Line drawings, black and white; 1 Halftones, black and white; 29 Tables, black and white; 165 Illustrations, black and white
  • Izdošanas datums: 31-Jul-2019
  • Izdevniecība: Productivity Press
  • ISBN-10: 1498759467
  • ISBN-13: 9781498759465
Citas grāmatas par šo tēmu:

This book is intended to be a cookbook for students and researchers to understand the finite element method and optimization methods and couple them to effect shape optimization. The optimization part of the book will survey optimization methods and focus on the genetic algorithm and Powell’s method for implementation in the codes. It will contain pseudo-code for the relevant algorithms and homework problems to reinforce the theory to compile finite element programs capable of shape optimization.

Features

  • Enables readers to understand the finite element method and optimization methods and couple them to effect shape optimization
  • Presents simple approach with algorithms for synthesis
  • Focuses on automated computer aided design (CAD) of electromagnetic devices
  • Provides a unitary framework involving optimization and numerical modelling
  • Discusses how to integrate open-source mesh generators into your code
  • Indicates how parallelization of algorithms, especially matrix solution and optimization, may be approached cheaply using the graphics processing unit (GPU) that is available on most PCs today
  • Includes coupled problem optimization using hyperthermia as an example
1 Analysis versus Design through Synthesis 2 Analysis in Electromagnetic Product Design 3 Optimization in Product Design - Synthesis 4 Some Basic Matrix Solution Schemes 5 Matrix Computation with Sparse Matrices 6 Other Formulations, Equations and Elements 7 Parametric Mesh Generation for Optimization 8 Parallelization through the Graphics Processing Unit 9 Coupled Problems
S. Ratnajeevan H. Hoole, B.Sc. Eng. Hons Cey., M.Sc. with Mark of Distinction London, Ph.D. Carnegie Mellon, is Professor of Electrical and Computer Engineering at Michigan State University in the US. For his accomplishments in electromagnetic product synthesis the University of London awarded him its higher doctorate, the D.Sc. (Eng.) degree, in 1993, and the IEEE elevated him to the grade of Fellow in 1995 with the citation "For contributions to computational methods for design optimization of electrical devices." His paper on using his inverse problem methods from design for NDE is widely cited, as is his paper on neural networks for the same purpose. These appear in The IEEE Transactions on Magnetics (1991 and 1993, respectively). He has authored 5 engineering texts published by Elsevier, another by Elsevier now carried by Prentice Hall, Oxford, Cambridge (India) and WIT Press. Prof. Hoole has been Vice Chancellor of University of Jaffna in Sri Lanka, and as Member of the University Grants Commission there, was responsible with six others for the regulation of the administration and academic standards of all 15 Sri Lankan universities and their admissions and funding. He has contributed widely to the learned literature on Tamil studies and been a regular columnist in newspapers. Prof. Hoole has been trained in Human Rights Research and Teaching at The Rene Cassin International Institute of Human Rights, Strasbourg, France, and has pioneered teaching human rights in the engineering curriculum. Yovahn Y. Ratnajeevan Hoole is a graduate student at the University of Illinois at Urbana Champaign. He holds a B.S. in Computer Science and a B.A. in Electrical Engineering from Rice University. He is currently working towards a doctorate in Electrical Engineering. His research interests are in Optimization, Machine Learning and their applications to real world engineering problems.