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A deterministic-particle-based scheme for micro-macro viscoelastic flows

delete2025-02-01
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包学莲 (Xuelian Bao)
刘春 封面图
刘春 (Chun Liu)
Y
Yiwei Wang *
DOI:10.1016/j.jcp.2024.113589delete
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摘要

摘要

En 中文
In this article, we introduce a new method for discretizing micro-macro models of dilute polymeric fluids by integrating a finite element method (FEM) discretization for the macroscopic fluid dynamics equation with a deterministic variational particle scheme for the microscopic Fokker-Planck equation. To address challenges arising from micro-macro coupling, we employ a discrete energetic variational approach to derive a coarse-grained micro-macro model with a particle approximation first and then develop a particle-FEM discretization for the coarse-grained model. The accuracy of the proposed method is evaluated for a Hookean dumbbell model in a Couette flow by comparing the computed velocity field with existing analytical solutions. We also use our method to study nonlinear FENE dumbbell models in different scenarios, such as extensional flow, pure shear flow, and lid-driven cavity flow. Numerical examples demonstrate that the proposed deterministic particle approach can accurately capture the various key rheological phenomena in the original FENE model, including hysteresis and S-function-like spike behavior in extensional flows, velocity overshoot phenomenon in pure shear flows, symmetries breaking, vortex center shifting, and vortices weakening in lid-driven cavity flows, with a small number of particles.
Keyword:
DILUTE POLYMER-SOLUTIONS
FINITE-ELEMENT APPROXIMATIONS
FOKKER-PLANCK EQUATION
DRIVEN CAVITY FLOW
CLOSURE APPROXIMATIONS
IRREVERSIBLE-PROCESSES
RECIPROCAL RELATIONS
HYSTERETIC BEHAVIOR
DUMBBELL MODEL
SIMULATIONS
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期刊

Journal of Computational Physics 封面图
Journal of Computational Physics
IF:
3.8
论文数:
1.6W
被引数:
7.4W

机构

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Illinois Institute of Technology
学者数:
3.8K
论文数: 3.9K
被引数: 4.2K
University of California System 封面图
University of California System
学者数:
37.5W
论文数: 33.7W
被引数: 6.6K
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south china university of technology
学者数:
6.8W
论文数: 5.1W
被引数: 85
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