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Proper Orthogonal Decomposition Methods for Partial Differential Equations (Mathematics in Science and Engineering) - Softcover

 
9780128167984: Proper Orthogonal Decomposition Methods for Partial Differential Equations (Mathematics in Science and Engineering)

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Proper Orthogonal Decomposition Methods for Partial Differential Equations evaluates the potential applications of POD reduced-order numerical methods in increasing computational efficiency, decreasing calculating load and alleviating the accumulation of truncation error in the computational process. Introduces the foundations of finite-differences, finite-elements and finite-volume-elements. Models of time-dependent PDEs are presented, with detailed numerical procedures, implementation and error analysis. Output numerical data are plotted in graphics and compared using standard traditional methods. These models contain parabolic, hyperbolic and nonlinear systems of PDEs, suitable for the user to learn and adapt methods to their own R&D problems.



  • Explains ways to reduce order for PDEs by means of the POD method so that reduced-order models have few unknowns
  • Helps readers speed up computation and reduce computation load and memory requirements while numerically capturing system characteristics
  • Enables readers to apply and adapt the methods to solve similar problems for PDEs of hyperbolic, parabolic and nonlinear types

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This guide evaluates the potential applications of the Proper Orthogonal Decomposition (POD) reduced-order numerical methods for time-dependent partial differential equations

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Proper Orthogonal Decomposition Methods for Partial Differential Equations evaluates the potential applications of POD reduced-order numerical methods in increasing computational efficiency, decreasing calculating load, and alleviating the accumulation of truncation error in the computational process. The work is self-contained. At the beginning of each chapter, the foundations of finite-differences, finite-elements and finite-volume-elements are introduced. Models are time-dependent PDEs are presented, with detailed numerical procedures, implementation and error analysis. Output numerical data are plotted in graphics and compared with those by the standard traditional methods. These models contain parabolic, hyperbolic and nonlinear systems of PDEs suitable for the user to learn and adapt methods to their own problems across research and development.

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  • PublisherAcademic Press
  • Publication date2018
  • ISBN 10 012816798X
  • ISBN 13 9780128167984
  • BindingPaperback
  • LanguageEnglish
  • Number of pages278

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Proper Orthogonal Decomposition Methods for Partial Differential Equations evaluates the potential applications of POD reduced-order numerical methods in increasing computational efficiency, decreasing calculating load and alleviating the accumulation of truncation error in the computational process. Introduces the foundations of finite-differences, finite-elements and finite-volume-elements. Models of time-dependent PDEs are presented, with detailed numerical procedures, implementation and error analysis. Output numerical data are plotted in graphics and compared using standard traditional methods. These models contain parabolic, hyperbolic and nonlinear systems of PDEs, suitable for the user to learn and adapt methods to their own R&D problems. Englisch. Seller Inventory # 9780128167984

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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Proper Orthogonal Decomposition Methods for Partial Differential Equations evaluates the potential applications of POD reduced-order numerical methods in increasing computational efficiency, decreasing calculating load and alleviating the accumulation of truncation error in the computational process. Introduces the foundations of finite-differences, finite-elements and finite-volume-elements. Models of time-dependent PDEs are presented, with detailed numerical procedures, implementation and error analysis. Output numerical data are plotted in graphics and compared using standard traditional methods. These models contain parabolic, hyperbolic and nonlinear systems of PDEs, suitable for the user to learn and adapt methods to their own R&D problems. Seller Inventory # 9780128167984

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