Literature DB >> 19355721

Bridging fluctuating hydrodynamics and molecular dynamics simulations of fluids.

Nikolaos K Voulgarakis1, Jhih-Wei Chu.   

Abstract

A new multiscale coarse-graining (CG) methodology is developed to bridge molecular and hydrodynamic models of a fluid. The hydrodynamic representation considered in this work is based on the equations of fluctuating hydrodynamics (FH). The essence of this method is a mapping from the position and velocity vectors of a snapshot of a molecular dynamics (MD) simulation to the field variables on Eulerian cells of a hydrodynamic representation. By explicit consideration of the effective lengthscale d(mol) that characterizes the volume of a molecule, the computed density fluctuations from MD via our mapping procedure have volume dependence that corresponds to a grand canonical ensemble of a cold liquid even when a small cell length (5-10 A) is used in a hydrodynamic representation. For TIP3P water at 300 K and 1 atm, d(mol) is found to be 2.4 A, corresponding to the excluded radius of a water molecule as revealed by its center-of-mass radial distribution function. By matching the density fluctuations and autocorrelation functions of momentum fields computed from solving the FH equations with those computed from MD simulation, the sound velocity and shear and bulk viscosities of a CG hydrodynamic model can be determined directly from MD. Furthermore, a novel staggered discretization scheme is developed for solving the FH equations of an isothermal compressive fluid in a three dimensional space with a central difference method. This scheme demonstrates high accuracy in satisfying the fluctuation-dissipation theorem. Since the causative relationship between field variables and fluxes is captured, we demonstrate that the staggered discretization scheme also predicts correct physical behaviors in simulating transient fluid flows. The techniques presented in this work may also be employed to design multiscale strategies for modeling complex fluids and macromolecules in solution.

Entities:  

Year:  2009        PMID: 19355721     DOI: 10.1063/1.3106717

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  6 in total

1.  Generalized Langevin dynamics of a nanoparticle using a finite element approach: thermostating with correlated noise.

Authors:  B Uma; T N Swaminathan; P S Ayyaswamy; D M Eckmann; R Radhakrishnan
Journal:  J Chem Phys       Date:  2011-09-21       Impact factor: 3.488

2.  An improved coarse-grained model of solvation and the hydrophobic effect.

Authors:  Patrick Varilly; Amish J Patel; David Chandler
Journal:  J Chem Phys       Date:  2011-02-21       Impact factor: 3.488

3.  Nanoparticle Brownian motion and hydrodynamic interactions in the presence of flow fields.

Authors:  B Uma; T N Swaminathan; R Radhakrishnan; D M Eckmann; P S Ayyaswamy
Journal:  Phys Fluids (1994)       Date:  2011-07-26       Impact factor: 3.521

4.  Computational Models for Nanoscale Fluid Dynamics and Transport Inspired by Nonequilibrium Thermodynamics.

Authors:  Ravi Radhakrishnan; Hsiu-Yu Yu; David M Eckmann; Portonovo S Ayyaswamy
Journal:  J Heat Transfer       Date:  2016-11-22       Impact factor: 2.021

5.  Concurrent multiscale modelling of atomistic and hydrodynamic processes in liquids.

Authors:  Anton Markesteijn; Sergey Karabasov; Arturs Scukins; Dmitry Nerukh; Vyacheslav Glotov; Vasily Goloviznin
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2014-08-06       Impact factor: 4.226

6.  Nanoparticle transport phenomena in confined flows.

Authors:  Ravi Radhakrishnan; Samaneh Farokhirad; David M Eckmann; Portonovo S Ayyaswamy
Journal:  Adv Heat Transf       Date:  2019-10-04
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.