High-Performance Computing of Big Data for Turbulence and Combustion
β Scribed by Sergio Pirozzoli, Tapan K. Sengupta
- Publisher
- Springer International Publishing
- Year
- 2019
- Tongue
- English
- Leaves
- 257
- Series
- CISM International Centre for Mechanical Sciences 592
- Edition
- 1st ed.
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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.
β¦ Table of Contents
Front Matter ....Pages i-ix
Focusing Phenomenon in Numerical Solution of Two-Dimensional NavierβStokes Equation (Tapan K. Sengupta, V. K. Suman)....Pages 1-29
Space-Time Resolution for Transitional and Turbulent Flows (Tapan K. Sengupta, Pushpender K. Sharma)....Pages 31-54
Finite Difference Methods for Incompressible and Compressible Turbulence (Sergio Pirozzoli)....Pages 55-118
Physical and Numerical Instabilities in Simulations of Reacting and Non Reacting Flows (Thierry Poinsot)....Pages 119-185
Low Rank Approximation of Multidimensional Data (Mejdi AzaΓ―ez, Lucas Lestandi, TomΓ‘s ChacΓ³n Rebollo)....Pages 187-250
β¦ Subjects
Engineering; Engineering Fluid Dynamics; Big Data
π SIMILAR VOLUMES
<P></P><B> <P>High-Performance Computing for Big Data: Methodologies and Applications </B>explores<B> </B>emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as
<P></P><B> <P>High-Performance Computing for Big Data: Methodologies and Applications </B>explores<B> </B>emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as
<span>An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning.<br>Β </span><span><br><br>Over the last decade, the exponential explosion of data known as </span><span>big data</span><span> has changed the way we understand and