Uncertainty Quantification in Computational Fluid Dynamics
Bijl, Hester (EDT); Lucor, Didier (EDT); Mishra, Siddharta (EDT); Schwab, Christoph (EDT)
ISBN 10: 3319008846 ISBN 13: 9783319008844
Published by Springer, 2013
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Fluid flows are characterized by uncertain inputs such as random initial data, material and flux coefficients, and boundary conditions. The current volume addresses the pertinent issue of efficiently computing the flow uncertainty, given this initial randomness. It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space. The methods are also complemented by concrete applications such as flows around aerofoils and rockets, problems of aeroelasticity (fluid-structure interactions), and shallow water flows for propagating water waves. The wealth of numerical examples provide evidence on the suitability of each proposed method as well as comparisons of different approaches.
From the Back Cover: Fluid flows are characterized by uncertain inputs such as random initial data, material and flux coefficients, and boundary conditions. The current volume addresses the pertinent issue of efficiently computing the flow uncertainty, given this initial randomness. It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space. The methods are also complemented by concrete applications such as flows around aerofoils and rockets, problems of aeroelasticity (fluid-structure interactions), and shallow water flows for propagating water waves. The wealth of numerical examples provide evidence on the suitability of each proposed method as well as comparisons of different approaches.
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Title: Uncertainty Quantification in Computational ...
Publisher: Springer
Publication Date: 2013
Binding: Hardcover
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Uncertainty Quantification in Computational Fluid Dynamics (Lecture Notes in Computational Science and Engineering, 92) [Hardcover] Bijl, Hester; Lucor, Didier; Mishra, Siddhartha and Schwab, Christoph (eng)
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Uncertainty Quantification in Computational Fluid Dynamics
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presentation of the highly relevant issue of UQ in CFDA broad spectrum of methods to efficiently compute uncertaintyLarge number of numerical examples as verification of the proposed methods and their possible comparisonFluid flows are ch. Seller Inventory # 4495982
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Uncertainty Quantification in Computational Fluid Dynamics
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Buch. Condition: Neu. Uncertainty Quantification in Computational Fluid Dynamics | Hester Bijl (u. a.) | Buch | xi | Englisch | 2013 | Springer | EAN 9783319008844 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 105660383
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Uncertainty Quantification in Computational Fluid Dynamics
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Fluid flows are characterized by uncertain inputs such as random initial data, material and flux coefficients, and boundary conditions. The current volume addresses the pertinent issue of efficiently computing the flow uncertainty, given this initial randomness. It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space. The methods are also complemented by concrete applications such as flows around aerofoils and rockets, problems of aeroelasticity (fluid-structure interactions), and shallow water flows for propagating water waves. The wealth of numerical examples provide evidence on the suitability of each proposed method as well as comparisons of different approaches. 333 pp. Englisch. Seller Inventory # 9783319008844
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Uncertainty Quantification in Computational Fluid Dynamics
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Fluid flows are characterized by uncertain inputs such as random initial data, material and flux coefficients, and boundary conditions. The current volume addresses the pertinent issue of efficiently computing the flow uncertainty, given this initial randomness. It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space. The methods are also complemented by concrete applications such as flows around aerofoils and rockets, problems of aeroelasticity (fluid-structure interactions), and shallow water flows for propagating water waves. The wealth of numerical examples provide evidence on the suitability of each proposed method as well as comparisons of different approaches. Seller Inventory # 9783319008844
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Uncertainty Quantification in Computational Fluid Dynamics
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Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Fluid flows are characterized by uncertain inputs such as random initial data, material and flux coefficients, and boundary conditions. The current volume addresses the pertinent issue of efficiently computing the flow uncertainty, given this initial randomness. It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space. The methods are also complemented by concrete applications such as flows around aerofoils and rockets, problems of aeroelasticity (fluid-structure interactions), and shallow water flows for propagating water waves. The wealth of numerical examples provide evidence on the suitability of each proposed method as well as comparisons of different approaches.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 356 pp. Englisch. Seller Inventory # 9783319008844
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Uncertainty Quantification in Computational Fluid Dynamics (Lecture Notes in Computational Science and Engineering, 92)
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