The Resource High-Performance Computing of Big Data for Turbulence and Combustion, edited by Sergio Pirozzoli, Tapan K. Sengupta, (electronic resource)

High-Performance Computing of Big Data for Turbulence and Combustion, edited by Sergio Pirozzoli, Tapan K. Sengupta, (electronic resource)

Label
High-Performance Computing of Big Data for Turbulence and Combustion
Title
High-Performance Computing of Big Data for Turbulence and Combustion
Statement of responsibility
edited by Sergio Pirozzoli, Tapan K. Sengupta
Contributor
Editor
Editor
Provider
Subject
Language
eng
Summary
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
Member of
http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsedt
  • uNK4Heyp73I
  • SYuWOPItOOs
Image bit depth
0
LC call number
TA357-359
Literary form
non fiction
http://library.link/vocab/relatedWorkOrContributorName
  • Pirozzoli, Sergio
  • Sengupta, Tapan K.
  • SpringerLink
Series statement
CISM International Centre for Mechanical Sciences, Courses and Lectures,
Series volume
592
http://library.link/vocab/subjectName
  • Hydraulic engineering
  • Big data
  • Engineering-Data processing
  • Engineering Fluid Dynamics
  • Big Data
  • Data Engineering
Label
High-Performance Computing of Big Data for Turbulence and Combustion, edited by Sergio Pirozzoli, Tapan K. Sengupta, (electronic resource)
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
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
Dimensions
unknown
Extent
IX, 250 p. 170 illus., 71 illus. in color.
File format
multiple file formats
Form of item
electronic
Isbn
9783030170127
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-030-17012-7
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-3-030-17012-7
Label
High-Performance Computing of Big Data for Turbulence and Combustion, edited by Sergio Pirozzoli, Tapan K. Sengupta, (electronic resource)
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
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
Dimensions
unknown
Extent
IX, 250 p. 170 illus., 71 illus. in color.
File format
multiple file formats
Form of item
electronic
Isbn
9783030170127
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-030-17012-7
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-3-030-17012-7

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