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Algorithmic methods dissipative particle dynamics

Carmesin, I. and Kremer, K. The bond fluctuation method a new effective algorithm for the dynamics of polymers in all spatial dimensions. Macromolecules, 21,2819-23 (1988). Hoogerbrugge, P. J. and Koelman, J. M. V. A. Simulating microscopic hydrodynamic phenomena with dissipative particle dynamics. Europhys Lett., 19,155-60 (1992). [Pg.249]

The CG method not only provides general models for studying a class of block copolymers but also conducts efficient algorithms for simulation. In this chapter, we overview the theoretical and computational approaches toward the simulations of dynamics of microphase separation of block copolymers with the focus on the recent contributions applying Monte Carlo (MC), dissipation particle dynamics... [Pg.283]

For the numerical simulation of flowing polymers, several mesoscopic models have been proposed in the last few years that describe polymer (hydro-)dynamics on a mesoscopic scale of several micrometers, typically. Among these methods, we like to mention dissipative particle dynamics (DPD) [168], stochastic rotation dynamics (sometimes also called multipartide collision dynamics) [33], and lattice Boltzmann algorithms [30]. Hybrid simulation schemes for polymer solutions have been developed recenfly, combining these methods for solvent dynamics with standard particle simulations of polymer beads (see Refs [32, 169, 170]). Extending the mesoscopic fluid models to nonideal fluids including polymer melts is currently in progress [30, 159,160,171]. [Pg.357]

One important feature of MFC algorithms is that the dynamics is well-defined for an arbitrary time step. At. In contrast to methods such as molecular dynamics simulations (MD) or dissipative particle dynamics (DFD), which approximate the continuous-time dynamics of a system, the time step does not have to be small. MFC defines a discrete-time dynamics which has been shown to yield the correct longtime hydrodynamics one consequence of the discrete dynamics is that the transport coefficients depend exphdtly on At. In fact, this freedom can be used to tune the Schmidt number. Sc [15] keeping all other parameters fixed, decreasing At leads to... [Pg.4]


See other pages where Algorithmic methods dissipative particle dynamics is mentioned: [Pg.39]    [Pg.205]    [Pg.138]    [Pg.610]    [Pg.201]    [Pg.334]    [Pg.386]   
See also in sourсe #XX -- [ Pg.730 , Pg.731 , Pg.732 ]




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