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Computationally intelligent cfd solving de bourisli raed (3 resultados)

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2010

    3843355193 / 9783843355193

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    Condición: Nuevo

    EUR 66,50

    Envío por EUR 70,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 5 disponibles

    Taschenbuch. Condición: Neu. Computationally Intelligent CFD | Solving Potential, Viscous and Non-Newtonian Fluid Flow Problems Using Real-Coded Genetic Algorithms | Raed Bourisli | Taschenbuch | 224 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783843355193 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2010

    3843355193 / 9783843355193

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    Librería: Mispah books, Redhill, SURRE, Reino UnidoMispah books

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    Condición: Usado - Como Nuevo

    EUR 205,78

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    Cantidad disponible: 1 disponible

    Paperback. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2010

    3843355193 / 9783843355193

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    • Impresión bajo demanda

    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 79,00

    Envío por EUR 35,00 
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    Cantidad disponible: 1 disponible

    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this work, the concept of evolutionary search is utilized as a versatile CFD solver. Specifically, a real-coded genetic algorithm, mimicking the natural evolution process, is used to minimize the residuals resulting from a finite difference discretization. While most gradient-based methods can suffer from divergence or slow convergence, the evolutionary solver's heuristic nature allows it to avoid solving the resulting systems of equations, thereby precluding many convergence difficulties and avoiding stiffness-related problems. Furthermore, these stochastic optimization techniques work around many stability issues in computational fluid dynamics. A number of new, unitary as well as binary, GA operators are proposed, explained and tested, along with the more traditional crossover and mutation operators. Also, new GA-customized refinement strategy and a GA-window approach are proposed which helps reduce time requirements. The GA is used to successfully solve problems involving a potential flow, a viscous flow via the Navier-Stokes equations, and a power-law non-Newtonian flow. The GA-solver is shown to be able to solve problems that the gradient-based method could not.…