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Proper Orthogonal Decomposition Methods by Luo Zhendong (17 results)
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Proper Orthogonal Decomposition Methods for Partial Differential Equations
Language: English
Published by Elsevier Science Publishing Co Inc, 2018
ISBN 10: 012816798X ISBN 13: 9780128167984
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 121.84
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Add to basketPaperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
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Proper Orthogonal Decomposition Methods for Partial Differential Equations
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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£ 126.40
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Proper Orthogonal Decomposition Methods for Partial Differential Equations (Mathematics in Science and Engineering)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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£ 136.17
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Taschenbuch. Condition: Neu. Proper Orthogonal Decomposition Methods for Partial Differential Equations | Zhendong Luo (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2018 | Academic Press | EAN 9780128167984 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Proper Orthogonal Decomposition Methods for Partial Differential Equations
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Proper Orthogonal Decomposition Methods for Partial Differential Equations
Language: English
Published by Elsevier Science Publishing Co Inc, US, 2018
ISBN 10: 012816798X ISBN 13: 9780128167984
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
£ 174.92
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Add to basketPaperback. Condition: New. 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 RandD problems.
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Proper Orthogonal Decomposition Methods for Partial Differential Equations
Language: English
Published by Elsevier Science Publishing Co Inc, US, 2018
ISBN 10: 012816798X ISBN 13: 9780128167984
£ 160.63
£ 65 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPaperback. Condition: New. 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 RandD problems.
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Condition: new. Questo è un articolo print on demand.
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Paperback. Condition: Brand New. 328 pages. 8.75x6.00x0.75 inches. In Stock. This item is printed on demand.
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Proper Orthogonal Decomposition Methods for Partial Differential Equations
Language: English
Published by Elsevier Science & Technology, Academic Press, 2018
ISBN 10: 012816798X ISBN 13: 9780128167984
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
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.
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Proper Orthogonal Decomposition Methods for Partial Differen
Language: English
Published by Elsevier Science & Technology|Academic Press, 2018
ISBN 10: 012816798X ISBN 13: 9780128167984
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 accumula.
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Proper Orthogonal Decomposition Methods for Partial Differential Equations
Language: English
Published by Elsevier Science & Technology, Academic Press, 2018
ISBN 10: 012816798X ISBN 13: 9780128167984
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.
