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High-performance computing of big da...

Pirozzoli, Sergio.

High-performance computing of big data for turbulence and combustion

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	High-performance computing of big data for turbulence and combustionedited by Sergio Pirozzoli, Tapan K. Sengupta.
其他作者:	Pirozzoli, Sergio.
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	ix, 250 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Turbulence.
電子資源:	https://doi.org/10.1007/978-3-030-17012-7
ISBN:	9783030170127$q(electronic bk.)

High-performance computing of big data for turbulence and combustion
High-performance computing of big data for turbulence and combustion[electronic resource] /edited by Sergio Pirozzoli, Tapan K. Sengupta. - Cham :Springer International Publishing :2019. - ix, 250 p. :ill., digital ;24 cm. - CISM international centre for mechanical sciences, courses and lectures,5920254-1971 ;. - CISM international centre for mechanical sciences, courses and lectures;592..

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 Instabilities in Simulations of Re-acting and non-Reacting Flows -- Low-Rank Approximation of Multidimensional Data.

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.

ISBN: 9783030170127$q(electronic bk.)

Standard No.: 10.1007/978-3-030-17012-7doiSubjects--Topical Terms:

188320
Turbulence.

LC Class. No.: TL574.T8 / .H544 2019

Dewey Class. No.: 629.1323

High-performance computing of big data for turbulence and combustion
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520 $a 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.
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