Discrete Models of Fluids: Spatial Averaging, Closure, and Model Reduction
Author(s) -
Alexander Panchenko,
Alexandre M. Tartakovsky,
Kevin D. Cooper
Publication year - 2014
Publication title -
siam journal on applied mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.954
H-Index - 99
eISSN - 1095-712X
pISSN - 0036-1399
DOI - 10.1137/12089346x
Subject(s) - ode , deconvolution , closure (psychology) , closure problem , microscale chemistry , large eddy simulation , mathematics , turbulence , nonlinear system , statistical physics , fluid dynamics , mathematical optimization , mechanics , algorithm , physics , mathematics education , quantum mechanics , economics , market economy
We consider semidiscrete ODE models of single-phase fluids and two-fluid mixtures. In the presence of multiple fine-scale heterogeneities, the size of these ODE systems can be very large. Spatial averaging is then a useful tool for reducing computational complexity of the problem. The averages satisfy exact balance equations of mass, momentum, and energy. These equations do not form a satisfactory continuum model because evaluation of stress and heat flux requires solving the underlying ODEs. To produce continuum equations that can be simulated without resolving microscale dynamics, we recently proposed a closure method based on the use of regularized deconvolution. Here we continue the investigation of deconvolution closure with the long term objective of developing consistent computational upscaling for multiphase particle methods. The structure of the fine-scale particle solvers is reminiscent of molecular dynamics. For this reason we use nonlinear averaging introduced for atomistic systems by Noll, Ha...
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom