Proper Generalized Decompositions: An Introduction to Computer Implementation with Matlab

Author:   Elías Cueto ,  David González ,  Icíar Alfaro
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2016
ISBN:  

9783319299938


Pages:   96
Publication Date:   10 March 2016
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Proper Generalized Decompositions: An Introduction to Computer Implementation with Matlab


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Overview

This book is intended to help researchers overcome the entrance barrier to Proper Generalized Decomposition (PGD), by providing a valuable tool to begin the programming task. Detailed Matlab Codes are included for every chapter in the book, in which the theory previously described is translated into practice. Examples include parametric problems, non-linear model order reduction and real-time simulation, among others. Proper Generalized Decomposition (PGD) is a method for numerical simulation in many fields of applied science and engineering. As a generalization of Proper Orthogonal Decomposition or Principal Component Analysis to an arbitrary number of dimensions, PGD is able to provide the analyst with very accurate solutions for problems defined in high dimensional spaces, parametric problems and even real-time simulation.   

Full Product Details

Author:   Elías Cueto ,  David González ,  Icíar Alfaro
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2016
Dimensions:   Width: 15.50cm , Height: 0.60cm , Length: 23.50cm
Weight:   1.766kg
ISBN:  

9783319299938


ISBN 10:   331929993
Pages:   96
Publication Date:   10 March 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Introduction.- 2 To begin with: PGD for Poisson problems.- 2.1 Introduction.- 2.2 The Poisson problem.- 2.3 Matrix structure of the problem.- 2.4 Matlab code for the Poisson problem.- 3 Parametric problems.- 3.1 A particularly challenging problem: a moving load as a parameter.- 3.2 The problem under the PGD formalism.- 3.2.1 Computation of S(s) assuming R(x) is known.- 3.2.2 Computation of R(x) assuming S(s) is known.- 3.3 Matrix structure of the problem.- 3.4 Matlab code for the influence line problem.- 4 PGD for non-linear problems.- 4.1 Hyperelasticity.- 4.2 Matrix structure of the problem.- 4.2.1 Matrix form of the term T2.- 4.2.2 Matrix form of the term T4.- 4.2.3 Matrix form of the term T6.- 4.2.4 Matrix form for the term T8.- 4.2.5 Matrix form of the term T9.- 4.2.6 Matrix form of the term T10.- 4.2.7 Final comments.- 4.3 Matlab code.- 5 PGD for dynamical problems.- 5.1 Taking initial conditions as parameters.- 5.2 Developing the weak form of the problem.- 5.3 Matrix form of the problem.- 5.3.1 Time integration of the equations of motion.- 5.3.2 Computing a reduced-order basis for the field of initial conditions.- 5.3.3 Projection of the equations onto a reduced, parametric basis.- 5.4 Matlab code.- References.- Index.

Reviews

This book provides a brief introduction to Proper Generalized Decompositions (PGD), with strong emphasis on computational aspects. The book discusses the implementation of PGD for the Poisson problem, parameter-dependent problems, linear-elasticity, and dynamical problems. For every problem, matrix assembly is developed and Matlab routines are presented. (Dante Kalise, Mathematical Reviews, July, 2017)


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