Separated Representations and PGD-Based Model Reduction Fundamentals and Applications

The papers in this volume start with a description of  the construction of reduced models through a review of Proper Orthogonal Decomposition (POD) and reduced basis models, including their mathematical foundations and some challenging applications, then followed by a description of a  new generatio...

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Detalles Bibliográficos
Autor Corporativo: SpringerLink (-)
Otros Autores: Chinesta, Francisco (-), Ladevèze, Pierre
Formato: Libro electrónico
Idioma:Inglés
Publicado: Vienna : Springer Vienna 2014.
Edición:1st ed
Colección:CISM International Centre for Mechanical Sciences ; 554.
Springer eBooks.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b32722229*spi
Descripción
Sumario:The papers in this volume start with a description of  the construction of reduced models through a review of Proper Orthogonal Decomposition (POD) and reduced basis models, including their mathematical foundations and some challenging applications, then followed by a description of a  new generation of simulation strategies based on the use of separated representations (space-parameters, space-time, space-time-parameters, space-space,…), which have led to what is known as Proper Generalized Decomposition (PGD) techniques. The models can be enriched by treating parameters as additional coordinates, leading to fast and inexpensive online calculations based on richer offline parametric solutions. Separated representations are analyzed in detail in the course, from their mathematical foundations to their most spectacular applications. It is also shown how such an approximation could evolve into a new paradigm in computational science, enabling one to circumvent various computational issues in a vast array of applications in engineering science.
Descripción Física:VII, 227 p., 74 il
Formato:Forma de acceso: World Wide Web.
ISBN:9783709117941