Viscous conducting flows with smooth-particle applied mechanics

Kum, Oyeon; Hoover, William G.; Posch, Harald A.

doi:10.1103/physreve.52.4899

Cited by 66 publications

(46 citation statements)

References 15 publications

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“…21 The weight function w 2 (r) is flat near the origin leading to small repulsive forces for small particle separations. This feature makes the system prone to forming lattice structures with several particles per site at high pressures, a problem common to SPH.…”

Section: ͑22͒mentioning

confidence: 99%

Thermodynamic consistency in dissipative particle dynamics simulations of strongly nonideal liquids and liquid mixtures

Trofimov

Nies

Michels

2002

The Journal of Chemical Physics

157

115

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Dissipative particle dynamics ͑DPD͒ is a mesoscopic simulation method for studying hydrodynamic behavior of complex fluids. Ideally, a mesoscopic model should correctly represent the thermo-and hydrodynamic properties of a real system beyond certain length and time scales. Traditionally defined DPD quite successfully mimics hydrodynamics, but is not flexible enough to accurately describe the thermodynamics of a real system. The so-called ''multibody'' DPD ͑MDPD͒ is a pragmatic extension of the classical DPD that allows one to prescribe the thermodynamic behavior of a system with only a small performance impact. Here we present a practical improvement to the ''multibody'' DPD model and test it on a number of single-component examples. We also generalize MDPD to multicomponent systems, which are an important target of DPD studies. The improved model provides a correction for particle correlations in strongly nonideal systems that were neglected in the original MDPD model. The implications of the coarse-graining procedure on the MDPD are discussed.

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Section: ͑22͒mentioning

confidence: 99%

Thermodynamic consistency in dissipative particle dynamics simulations of strongly nonideal liquids and liquid mixtures

Trofimov

Nies

Michels

2002

The Journal of Chemical Physics

157

115

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“…The comparison of SPD with the fluid particle model points out to an inconsistency that appears when using some particular selections for the weight function like the Lucy weight function [5] or a Gaussian weight function [3]. In these cases, it is easily seen that the function A(r) can become negative for certain values of r. This is unacceptable in view of Eqn.…”

Section: Resolution Issues Of the Fluid Particle Modelmentioning

confidence: 86%

“…Another advantage of a Lagrangian description relies on the fact that no expensive recalculations of the mesh are required as the dynamics takes care of it. Smoothed particle dynamics has been used for simulating astrophysical flows with non-viscous terms (this was the original aim of the technique at the early 70's [2]), and very recently in the study of viscous [3,4] and thermal flows [5,6] in simple geometries. It has not been applied to the study of complex fluids and this may be due, in part, to the fact that there is no easy implementation of Lagrangian fluctuating hydrodynamics [7] with SPD.…”

Section: Introductionmentioning

confidence: 99%

Fluid particle model

1998

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We present a mechanistic model for a Newtonian fluid called fluid particle dynamics. By analyzing the concept of "fluid particle" from the point of view of a Voronoi tessellation of a molecular fluid, we propose an heuristic derivation of a dissipative particle dynamics algorithm that incorporates shear forces between dissipative particles. The inclusion of these non-central shear forces requires the consideration of angular velocities of the dissipative particles in order to comply with the conservation of angular momentum. It is shown that the equilibrium statistical mechanics requirement that the linear and angular velocity fields are Gaussian is sufficient to construct the random thermal forces between dissipative particles. The proposed algorithm is very similar in structure to the (isothermal) smoothed particle dynamics algorithm. In this way, this work represents a generalization of smoothed particle dynamics that incorporates consistently thermal fluctuations and exact angular momentum conservation. It contains also the dissipative particle dynamics algorithm as a special case. Finally, the kinetic theory of the dissipative particles is derived and explicit expressions of the transport coefficients of the fluid in terms of model parameters are obtained. This allows to discuss resolution issues for the model.

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“…A recent particle approach to macroscopic simulation, smooth particle applied mechanics [3,4], has revealed new links between the reversibility paradox which separates classical mechanics from thermodynamics, and promises assistance in understanding the irreversibility inherent in turbulent flows. Here we discuss the concepts of temperature, heat transfer, Lyapunov instability, and turbulence, in order to enhance the understanding of the connections among them.…”

Section: 2]mentioning

confidence: 99%