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DPD code

The cut-off radius rc t is defined arbitrarily and reveals the range of interaction between the fluid particles. DPD model with longer cut-off radius reproduces better dynamical properties of realistic fluids expressed in terms of velocity correlation function [80]. Simultaneously, for a shorter cut-off radius, the efficiency of DPD codes increases as 0(1 /t ut). which allows for more precise computation of thermodynamic properties of the particle system from statistical mechanics point of view. A strong background drawn from statistical mechanics has been provided to DPD [43,80,81] from which explicit formulas for transport coefficients in terms of the particle interactions can be derived. The kinetic theory for standard hydrodynamic behavior in the DPD model was developed by Marsh et al. [81] for the low-friction (small value of yin Equation (26.25)), low-density case and vanishing conservative interactions Fc. In this weak scattering theory, the interactions between the dissipative particles produce only small deflections. [Pg.732]

DPD codes are usually simple modifications of molecular dynamics (MD) programs, and since this latter correlation is inconvenient for algorithms with a finite time step h, the actual random number to be used in the nth step becomes ,>( ) = Gy(t)dt. Clearly, y(n)) =0 and f (n)) =h, while... [Pg.561]

A DPD simulation may involve as few as 1000 particles for siirple equilibrium simulations to several million particles for simulations of complex fluids. Hence, it is important to run DPD codes in a parallel environment. There are several parallelization strategies, such as domain decomposition and force decomposition methods. One method that is appealing because of the particle-based nature of the method is the atom decomposition algorithm in which the computations for the N particles are split among P processors. Further advantage can be taken from the fact that DPD is a short-range method, i. e. each particle does... [Pg.389]

The numerical schemes used for integration of the Newtonian equations of motion. Stable, accurate and efficient schemes are in great demand. Unlike in the standard MD codes, in FPM and DPD due to the random Brownian force, the equations of motion are stochastic... [Pg.742]

Furthermore, it is expected that DPD will play an ever-increasing role in multi-scale modeling approaches through bridging of the atomistic and continuum scales. In such approaches, atomistic simulations are performed to build the DPD models, followed by DPD simulations which provide the necessary input to the continuum codes. [Pg.26]

As with an atomistic study, the approach taken to calculate viscosity with DPD is to simulate Poiseuille flow between two infinite parallel plates, to measure the velocity of the fluid within the plates, and then to apply the Navier-Stokes method to calculate the fluid s viscosity from the velocity. DPD simulations were solved using an Open MPI compiled version of the Sandia National Laboratory LAMMPS code... [Pg.337]


See other pages where DPD code is mentioned: [Pg.531]    [Pg.620]    [Pg.23]    [Pg.436]    [Pg.562]    [Pg.531]    [Pg.620]    [Pg.23]    [Pg.436]    [Pg.562]    [Pg.134]    [Pg.291]    [Pg.291]    [Pg.63]    [Pg.9]    [Pg.419]    [Pg.722]    [Pg.769]    [Pg.307]    [Pg.610]    [Pg.344]   
See also in sourсe #XX -- [ Pg.531 ]




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DPD

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