Abstract
Dissipative Particle Dynamics (DPD) has been recognized as a powerful tool for simulating the dynamics of complex fluids on a mesoscopic scale. However, owing to the rigid thermodynamic behavior of the standard model, it has limitations when applied to real systems. Although refined models have been developed to improve the thermodynamic consistency of DPD, they are not without limitations and deficiencies. In this paper, we extend the power of DPD beyond its traditional limits so that it can cope with systems where temperature and pressure changes occur. This is accomplished using a refined model termed Flexible DPD (FDPD), which allows the equation of state (EOS) to be given in priori. As a basis for the development of FDPD, the generalized expression for the thermodynamic variables is derived by solving the Langevin equation of a particle. It is found that the radial distribution function will be approximately invariant under variable transformation if the action range of potential is changed appropriately according to local density. With this invariant character of RDF, and by choosing the force functions to be variable separable, equations relating thermodynamic variables with the functions for DPD interactions are derived, and the weighting function for achieving thermodynamic is designed correspondingly. A case study on the validation of the FDPD method has been undertaken on the adiabatic compression of N2gas. The simulation results were compared with the theoretical predictions as well as to the simulation results of the ordinary DPD method. The invariant of radial distribution function is justified by the results of the simulation.
Original language | English |
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Pages (from-to) | 1129-1148 |
Number of pages | 20 |
Journal | International Journal of Modern Physics C |
Volume | 21 |
Issue number | 9 |
DOIs | |
Publication status | Published - 1 Sept 2010 |
Keywords
- Dissipative particle dynamics
- mesoscopic sim-ulation
- thermodynamic consistency
ASJC Scopus subject areas
- Statistical and Nonlinear Physics
- Mathematical Physics
- Physics and Astronomy(all)
- Computer Science Applications
- Computational Theory and Mathematics