A compressible fluid particle model based on the Voronoi ...

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Motivation Complex <strong>fluid</strong>s Coupling between the microstructure and the hydrodynamic variables of the <strong>fluid</strong> The thermal fluctuations are the responsible of the diffusive processes Lagrangian methods are adaptative to the complex boundary conditions involved in complex <strong>fluid</strong>s dynamics The main objective of this work is the formulation of Lagrangian simulation techniques and hydrodynamic <strong>model</strong>s that are able to represent simple and complex <strong>fluid</strong>s in the mesoscopic scale consistent with Thermodynamics
SPH Discretization of continuum hydrodynamics in Lucy, Astron. J. 1977 Monaghan ,An. Rev. terms of <strong>particle</strong>s transforming PDE into ODE Astron. Astrophys. 1992 DPD Mesoscopic <strong>model</strong> of interacting <strong>fluid</strong> <strong>particle</strong>s via conservative, dissipative, random forces Hoogerbrugge Koelman, Europhys. Lett. 1992 Español, Bonet Europhys.Lett. 1997 SDPD SDPD VORONOI With the help of the GENERIC formalism we Serrano, Español, Phys. Rev. E 2001 Lagrangian techniques How to include thermal fluctuations? What is the volume? Different implementations? Conservative forces? Thermodynamic behaviour? Relation between transport coeff. and <strong>model</strong> parameters? SDPD technique considered as <strong>fluid</strong> <strong>particle</strong> <strong>model</strong>s with “soft”volumes Español, Revenga Phys Rev E 2003 We extract the best: -fluctuations from DPD -connection to NS from SPH build a new mesoscopic <strong>fluid</strong> <strong>particle</strong> <strong>model</strong> with “sharp” volumes. This <strong>model</strong> represents the discrete Lagrangian fluctuating hydrodynamics
Page 1 and 2: A compressible <st
Page 3: Outline 1. Motivacion: Lagrangian t
Page 7 and 8: Mesoscopic fluid <
Page 9 and 10: Outline 1. Motivacion: Lagrangian t
Page 11 and 12: m i dVi dt This dynamics can be und
Page 13 and 14: Voronoi Ri Aij Rij Rj cij eij lim
Page 17 and 18: Spatial derivatives SDPD/Voronoi
Page 19 and 20: 2 m i Ex ( ) = ∑ + ε ( mi, Si, v
Page 21 and 22: Including thermal fluctuations ⎛
Page 23 and 24: y Comparing the performance of SDPD
Page 25 and 26: Stationary velocity profiles Disord
Page 29: Conclusions -The discrete m
Page 33 and 34: 2d implementation Structure of the
Page 35 and 36: OLD TOPOLOGY Fik Fil v1 i j v2 Time
Page 37 and 38: Properties of the non dissipative V
Page 39: SDPD Overlapping Input theory s=3 s

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