Stochastic mode reduction for particle-based simulation methods for complex microfluid systems

AJ Majda, PR Kramer - SIAM Journal on Applied Mathematics, 2004 - SIAM
AJ Majda, PR Kramer
SIAM Journal on Applied Mathematics, 2004SIAM
We illustrate the stochastic mode reduction procedure as formulated recently by Majda,
Timofeyev, and Vanden-Eijnden [Comm. Pure Appl. Math., 54 (2001), pp. 891--974](MTV)
on the equations of motion underlying various particle-based simulation approaches (such
as Stokesian dynamics and Brownian dynamics) and the conceptually distinct dissipative
particle dynamics (DPD) simulation approaches for complex microfluid systems. The
resulting coarse-grained dynamics are compared and contrasted with each other. We show …
We illustrate the stochastic mode reduction procedure as formulated recently by Majda, Timofeyev, and Vanden-Eijnden [Comm. Pure Appl. Math., 54 (2001), pp. 891--974] (MTV) on the equations of motion underlying various particle-based simulation approaches (such as Stokesian dynamics and Brownian dynamics) and the conceptually distinct dissipative particle dynamics (DPD) simulation approaches for complex microfluid systems. The resulting coarse-grained dynamics are compared and contrasted with each other. We show that the stochastic mode reduction procedure provides a way to recover the Smoluchowski dynamics for a standard model of multiple interacting particles in a fluid. The DPD, however, has some subtle aspects which obstruct the application of the stochastic mode reduction procedure. We discuss the mathematical and physical properties of the DPD method that underlie thisdifficulty.
Society for Industrial and Applied Mathematics
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