43,210 research outputs found
Stochastic Hard-Sphere Dynamics for Hydrodynamics of Non-Ideal Fluids
A novel stochastic fluid model is proposed with non-ideal structure factor
consistent with compressibility, and adjustable transport coefficients. This
Stochastic Hard Sphere Dynamics (SHSD) algorithm is a modification of the
Direct Simulation Monte Carlo (DSMC) algorithm and has several computational
advantages over event-driven hard-sphere molecular dynamics. Surprisingly, SHSD
results in an equation of state and pair correlation function identical to that
of a deterministic Hamiltonian system of penetrable spheres interacting with
linear core pair potentials. The fluctuating hydrodynamic behavior of the SHSD
fluid is verified for the Brownian motion of a nano-particle suspended in a
compressible solvent.Comment: This work performed under the auspices of the U.S. Department of
Energy by Lawrence Livermore National Laboratory under Contract
DE-AC52-07NA27344 (LLNL-JRNL-401745). To appear in Phys. Rev. Lett. 200
Stochastic boundary conditions for molecular dynamics simulations
In this paper we develop a stochastic boundary conditions (SBC) for
event-driven molecular dynamics simulations of a finite volume embedded within
an infinite environment. In this method, we first collect the statistics of
injection/ejection events in periodic boundary conditions (PBC). Once
sufficient statistics are collected, we remove the PBC and turn on the SBC. In
the SBC simulations, we allow particles leaving the system to be truly ejected
from the simulation, and randomly inject particles at the boundaries by
resampling from the injection/ejection statistics collected from the current or
previous simulations. With the SBC, we can measure thermodynamic quantities
within the grand canonical ensemble, based on the particle number and energy
fluctuations. To demonstrate how useful the SBC algorithm is, we simulated a
hard disk gas and measured the pair distribution function, the compressibility
and the specific heat, comparing them against literature values.Comment: 24 pages, 16 figure
The Two Regime method for optimizing stochastic reaction-diffusion simulations
The computer simulation of stochastic reaction-diffusion processes in biology is often done using either compartment-based (spatially discretized) simulations or molecular-based (Brownian dynamics) approaches. Compartment-based approaches can yield quick and accurate mesoscopic results but lack the level of detail that is characteristic of the more computationally intensive molecular-based models. Often microscopic detail is only required in a small region but currently the best way to achieve this detail is to use a resource intensive model over the whole domain. We introduce the Two Regime Method (TRM) in which a molecular-based algorithm is used in part of the computational domain and a compartment-based approach is used elsewhere in the computational domain. We apply the TRM to two test problems including a model from developmental biology. We thereby show that the TRM is accurate and subsequently may be used to inspect both mesoscopic and microscopic detail of reaction diffusion simulations according to the demands of the modeller
A Thermodynamically-Consistent Non-Ideal Stochastic Hard-Sphere Fluid
A grid-free variant of the Direct Simulation Monte Carlo (DSMC) method is
proposed, named the Isotropic DSMC (I-DSMC) method, that is suitable for
simulating dense fluid flows at molecular scales. The I-DSMC algorithm
eliminates all grid artifacts from the traditional DSMC algorithm; it is
Galilean invariant and microscopically isotropic. The stochastic collision
rules in I-DSMC are modified to yield a non-ideal structure factor that gives
consistent compressibility, as first proposed in [Phys. Rev. Lett. 101:075902
(2008)]. The resulting Stochastic Hard Sphere Dynamics (SHSD) fluid is
empirically shown to be thermodynamically identical to a deterministic
Hamiltonian system of penetrable spheres interacting with a linear core pair
potential, well-described by the hypernetted chain (HNC) approximation. We
apply a stochastic Enskog kinetic theory for the SHSD fluid to obtain estimates
for the transport coefficients that are in excellent agreement with particle
simulations over a wide range of densities and collision rates. The fluctuating
hydrodynamic behavior of the SHSD fluid is verified by comparing its dynamic
structure factor against theory based on the Landau-Lifshitz Navier-Stokes
equations. We also study the Brownian motion of a nano-particle suspended in an
SHSD fluid and find a long-time power-law tail in its velocity autocorrelation
function consistent with hydrodynamic theory and molecular dynamics
calculations.Comment: 30 pages, revision adding some clarifications and a new figure. See
also arXiv:0803.035
- …