Proper Generalized Decompositions: An Introduction to Computer Implementation with Matlab (SpringerBriefs in Applied Sciences and Technology) - Softcover

Cueto, Elías; González, David; Alfaro, Icíar

Softcover

ISBN 10: 331929993X ISBN 13: 9783319299938

Verlag: Springer, 2016

Inhaltsangabe

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.

  

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Über die Autorin bzw. den Autor

Elías Cueto is professor of continuum and structural mechanics at the university of Zaragoza since 2010. His research has been devoted to the development of advanced numerical strategies for the simulation of complex phenomena. In particular, in the last years he has worked in model order reduction techniques and real-time simulation for computational surgery and augmented reality applications. His work has been recognized with the J. C. Simo award of the Spanish Society of Numerical Methods in Engineering, the European Scientific Association of Material Forming (ESAFORM) Scientific Prize, and the O.C. Zienkiewicz prize of the European Community on Computational Methods in Applied Sciences, ECCOMAS, among others. He has published more than one hundred papers in the field and is from 2016 president of the Spanish Society of Numerical Methods in Engineering (SEMNI).

David González is Associate Professor of Continuum Mechanics in the Mechanical Engineering Department of the University of Zaragoza. His research activity focuses mainly on the development of numerical methods for the simulation of multi-scale and multi-physics problems in the fields of applied sciences and engineering. This includes the development or the improvement at the theoretical level of techniques such as the Natural Element Method. More recently, the work of Prof. González has centred on the development of numerical techniques for multiscale simulation of materials, both solids and liquids. This line of research is based on the use of model reduction techniques, such as the Proper Generalized Decomposition (PGD) technique. These kinds of techniques allow the efficient simulating of problems defined in very high dimensional spaces (Schroedinger eq., kinetic theory approaches, among others). He has published more than fifty papers in the field.

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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.  

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2016
• Sprache: Englisch
• ISBN 10: 331929993X
• ISBN 13: 9783319299938
• Einband: Taschenbuch
• Auflage: 1
• Anzahl der Seiten: 108
• Kontakt zum Hersteller: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Deutschland