Titlebook: High-Performance Computing of Big Data for Turbulence and Combustion; Sergio Pirozzoli,Tapan K. Sengupta Book 2019 CISM International Cent

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Finite Difference Methods for Incompressible and Compressible Turbulence,olds number and on ‘non-classical’ effects associated with the formation of large rollers (Couette flow), and with compressibility effects. The behavior of passive scalars advected by the fluid phase is also discussed.

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乏味

,Focusing Phenomenon in Numerical Solution of Two-Dimensional Navier–Stokes Equation,e process, we identify critical numerical Peclet number for a chosen CFL number. We show virtually, one to one correspondence between the . of convection-diffusion equation with abrupt blow up the numerical solution of the Navier–Stokes equation.

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Low Rank Approximation of Multidimensional Data,s studied, including discussions on the equivalence of proper orthogonal decomposition (POD, continuous framework) and singular value decomposition (SVD, discrete matrices). Then, in the second part, a wide review of tensor formats and their approximation is proposed. Such work has already been prov

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0254-1971 raisethe 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 general978-3-030-17014-1978-3-030-17012-7Series ISSN 0254-1971 Series E-ISSN 2309-3706

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High-Performance Computing of Big Data for Turbulence and Combustion

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Mejdi Azaïez,Lucas Lestandi,Tomás Chacón Rebolloweisen sich für die Bewältigung der aktuellen situativen Rahmenbedingungen als immer weniger geeignet, da gesicherte, langfristige Vorhersagen als Planungsbasis immer schwieriger, wenn nicht fast unmöglich werden. Innovative Strategien zur Anpassung der Unternehmensorganisation an die veränderten Ra

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https://doi.org/10.1007/978-3-030-17012-7high-accuracy numerical methods; DNS of turbulence and combustion; high-performance computing; big data