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Computational Aspects of Multiscale Simulation with the Lumped Particle Framework

Published online by Cambridge University Press:  20 August 2015

Omar al-Khayat  and
Hans Petter Langtangen
Omar al-Khayat*
Affiliation:
Computational Geosciences, CBC, Simula Research Laboratory, P.O. Box 134, NO-1325 Lysaker, Norway
Hans Petter Langtangen*
Affiliation:
Department of Informatics, University of Oslo, P.O. Box 1080, Blindern, NO-0316 Oslo, Norway Center for Biomedical Computing, Simula Research Laboratory, P.O. Box 134, NO-1325 Lysaker, Norway
*
Corresponding author.Email:[email protected]
Email:[email protected]
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Abstract

First introduced in, the lumped particle framework is a flexible and numerically efficient framework for the modelling of particle transport in fluid flow. In this paper, the framework is expanded to simulate multicomponent particle-laden fluid flow. This is accomplished by introducing simulation protocols to model particles over a wide range of length and time scales. Consequently, we present a time ordering scheme and an approximate approach for accelerating the computation of evolution of different particle constituents with large differences in physical scales. We apply the extended framework on the temporal evolution of three particle constituents in sandladen flow, and horizontal release of spherical particles. Furthermore, we evaluate the numerical error of the lumped particle model. In this context, we discuss the Velocity-Verlet numerical scheme, and show how to apply this to solving Newton’s equations within the framework. We show that the increased accuracy of the Velocity-Verlet scheme is not lost when applied to the lumped particle framework.

Keywords

65L1265L7068W2586-0834E1334E99Multiscale modellinglumped particle modelVelocity-Verlet scheme
Type
Research Article
Information
Communications in Computational Physics , Volume 12 , Issue 4 , October 2012 , pp. 1257 - 1274
Copyright
Copyright © Global Science Press Limited 2012

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References

[1]Aarnes, J. E., Kippe, V., and Lie, K-A.. Mixed multiscale finite elements and streamline methods for reservoir simulation of large geomodels. Advances in Water Resources, 28(3):257–271, 2005.Google Scholar
[2]al Khayat, O., Bruaset, A. M., and Langtangen, H. P.. A lumped particle modeling framework for simulating particle transport in fluids. Communication in Computational Physics, 8(1):115–142, 2010.Google Scholar
[3]al Khayat, O., Bruaset, A. M., and Langtangen, H. P.. Particle collisions in a lumped particle model. Communication in Computational Physics, 10(4):823–843, 2010.Google Scholar
[4]Neufeld, J.. The experimental nonlinear physics group, the university of toronto. http://www.physics.utoronto.ca/nonlin/turbidity/turbidity.html, 2007.Google Scholar
[5]Ren, W. and W. E., Heterogeneous multiscale method for the modeling of complex fluids and micro-fluidics. Journal of Computational Physics, 204(1):1–26, 2005.Google Scholar
[6]Swope, W. C., Andersen, H. C., Berens, P. H., and Wilson, K. R.. A computer simulation method for the calculation of equilibrium constants for the formation of physical clusters of molecules: Application to small water clusters. The Journal of Chemical Physics, 76(1):637–649, 1982.Google Scholar
[7]Tuckerman, M. E., Berne, B. J., and Rossi, A.. Molecular dynamics algorithm for multiple time scales: Systems with disparate masses. Journal of Chemical Physics, 94(2):1465–1469, 1991.Google Scholar