Spatially adaptive stochastic methods for fluid-structure interactions subject to thermal fluctuations in domains with complex geometries

Plunkett, Pat; Hu, Jonathan; Siefert, Christopher; Atzberger, Paul J.

doi:10.1016/j.jcp.2014.07.051

Spatially adaptive stochastic methods for fluid-structure interactions subject to thermal fluctuations in domains with complex geometries

Journal Article · Thu Aug 07 04:00:00 EDT 2014 · Journal of Computational Physics

DOI:https://doi.org/10.1016/j.jcp.2014.07.051· OSTI ID:1226084

Plunkett, Pat ^[1]; Hu, Jonathan ^[2]; Siefert, Christopher ^[2]; ^[1]

Univ. of California, Santa Barbara, CA (United States)
Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Sandia National Laboratories, Albuquerque, NM (United States)

We develop stochastic mixed finite element methods for spatially adaptive simulations of fluid–structure interactions when subject to thermal fluctuations. To account for thermal fluctuations, we introduce a discrete fluctuation–dissipation balance condition to develop compatible stochastic driving fields for our discretization. We also perform analysis that shows our condition is sufficient to ensure results consistent with statistical mechanics. We show the Gibbs–Boltzmann distribution is invariant under the stochastic dynamics of the semi-discretization. To generate efficiently the required stochastic driving fields, we develop a Gibbs sampler based on iterative methods and multigrid to generate fields with O(N) computational complexity. Our stochastic methods provide an alternative to uniform discretizations on periodic domains that rely on Fast Fourier Transforms. To demonstrate in practice our stochastic computational methods, we investigate within channel geometries having internal obstacles and no-slip walls how the mobility/diffusivity of particles depends on location. Furthermore, our methods extend the applicability of fluctuating hydrodynamic approaches by allowing for spatially adaptive resolution of the mechanics and for domains that have complex geometries relevant in many applications.

Research Organization:: Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Sandia National Laboratories, Albuquerque, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

DOE Contract Number:: AC04-94AL85000

OSTI ID:: 1226084

Report Number(s):: SAND--2015-9349J; 607831

Journal Information:: Journal of Computational Physics, Journal Name: Journal of Computational Physics Journal Issue: C Vol. 277; ISSN 0021-9991

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

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Brownian Dynamics of Fully Confined Suspensions of Rigid Particles Without Green's Functions Sprinkle, Brennan; Donev, Aleksandar; Bhalla, Amneet Pal Singh arXiv https://doi.org/10.48550/arxiv.1901.06427	text	January 2019
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