Sergio Pirozzoli; Tapan K. Sengupta High-Performance Computing of Big Data for Turbulence and Combustion 9783030170110

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Автор: Sergio Pirozzoli; Tapan K. Sengupta
Название: High-Performance Computing of Big Data for Turbulence and Combustion
ISBN: 9783030170110
Издательство: Springer
Классификация:

Шекспироведение и критика

Материаловедение

Механика текучих сред

Базы данных

ISBN-10: 303017011X
Обложка/Формат: Hardcover
Страницы: 250
Вес: 0.56 кг.
Дата издания: 2019
Серия: CISM International Centre for Mechanical Sciences
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 71 illustrations, color; 99 illustrations, black and white; ix, 250 p. 170 illus., 71 illus. in color.
Размер: 234 x 156 x 16
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book provides state-of-art information on high-accuracy scientific computing and its future prospects, as applicable to the broad areas of fluid mechanics and combustion, and across all speed regimes. Beginning with the concepts of space-time discretization and dispersion relation in numerical computing, the foundations are laid for the efficient solution of the Navier-Stokes equations, with special reference to prominent approaches such as LES, DES and DNS. The basis of high-accuracy computing is rooted in the concept of stability, dispersion and phase errors, which require the comprehensive analysis of discrete computing by rigorously applying error dynamics. In this context, high-order finite-difference and finite-volume methods are presented. Naturally, the coverage also includes fundamental notions of high-performance computing and advanced concepts on parallel computing, including their implementation in prospective hexascale computers. Moreover, the book seeks to raise the bar beyond the pedagogical use of high-accuracy computing by addressing more complex physical scenarios, including turbulent combustion. Tools like proper orthogonal decomposition (POD), proper generalized decomposition (PGD), singular value decomposition (SVD), recursive POD, and high-order SVD in multi-parameter spaces are presented. Special attention is paid to bivariate and multivariate datasets in connection with various canonical flow and heat transfer cases. The book mainly addresses the needs of researchers and doctoral students in mechanical engineering, aerospace engineering, and all applied disciplines including applied mathematics, offering these readers a unique resource.
Дополнительное описание:

Focusing Phenomenon in Numerical Solution of Two-Dimensional Navier-Stokes Equation.- Space-Time Resolution for Transitional and Turbulent Flows.- Finite Difference Methods for Incompressible and Compressible Turbulence.- Physical and Numerical Insta

High-Performance Computing of Big Data for Turbulence and Combustion, Sergio Pirozzoli; Tapan K. Sengupta