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arXiv 2406.04722physics.flu-dynphysics.comp-ph
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物理一致的浸入边界方法:一种在粗网格上预测颗粒流体动力的框架

Physically consistent immersed boundary method: a framework for predicting hydrodynamic forces on particles with coarse meshes

Max Hausmann, Hani Elmestikawy, Berend van Wachem

AI总结:

本文提出一种物理一致的浸入边界方法(PC-IBM),通过体积过滤推导并兼容大涡模拟,在粗网格下准确预测颗粒流体动力,阻力偏差小于10%。

摘要:

本文通过应用体积过滤的概念,直接从 Navier-Stokes 方程(NSE)推导出一种流固耦合方法,产生了一种物理一致的方法,将固壁边界条件纳入体积过滤的流动解中,从而允许在非贴体网格上求解控制流动方程。由此产生的方法与连续力浸入边界方法(IBM)具有相似性,因此被称为物理一致的 IBM(PC-IBM)。基于 arXiv:2402.05842v1 的最新发现,体积过滤 NSE 中出现的闭合项通过合适的模型进行闭合,甚至可以解析表达。PC-IBM 与大涡模拟框架完全兼容,因为在远离固体边界处,体积过滤的 NSE 收敛于过滤后的 NSE。通过不同的含颗粒流动应用,包括固定颗粒的密集堆积和 500 个颗粒的周期沉降,展示了 PC-IBM 的潜力。新方法能够准确预测较粗网格分辨率下颗粒受到的流体作用力。对于孤立球体绕流,每直径 6 个流体网格单元的空间分辨率足以预测阻力,在 10 到 250 的颗粒雷诺数范围内,与高分辨率模拟的偏差小于 10%。

英文摘要:

In the present paper, a fluid-particle coupling method is directly derived from the Navier-Stokes equations (NSE) by applying the concept of volume-filtering, yielding a physically consistent methodology to incorporate solid wall boundary conditions in the volume-filtered flow solution, thereby allowing to solve the governing flow equations on non-body conforming meshes. The resulting methodology possesses similarities with a continuous forcing immersed boundary method (IBM) and is, therefore, termed physically consistent IBM (PC-IBM). Based on the recent findings of arXiv:2402.05842v1, the closures arising in the volume-filtered NSE are closed by suitable models or even expressed analytically. The PC-IBM is fully compatible with the large eddy simulation framework, as the volume-filtered NSE converge to the filtered NSE away from solid boundaries. The potential of the PC-IBM is demonstrated by means of different particle-laden flow applications, including a dense packing of fixed particles and periodic settling of 500 particles. The new methodology turns out to be capable of accurately predicting the fluid forces on particles with relatively coarse mesh resolutions. For the flow around isolated spheres, a spatial resolution of six fluid mesh cells per diameter is sufficient to predict the drag force with less than 10% deviation from highly resolved simulation for the investigated particle Reynolds numbers ranging from 10 to 250.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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