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SPARSE—A subgrid particle averaged Reynolds stress equivalent model: testing with a priori closure

机译:SPARSE-亚网格平均雷诺应力等效模型:先验封闭测试

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摘要

A Lagrangian particle cloud model is proposed that accounts for the effects of Reynolds-averaged particle and turbulent stresses and the averaged carrier-phase velocity of the subparticle cloud scale on the averaged motion and velocity of the cloud. The SPARSE (subgrid particle averaged Reynolds stress equivalent) model is based on a combination of a truncated Taylor expansion of a drag correction function and Reynolds averaging. It reduces the required number of computational parcels to trace a cloud of particles in Eulerian–Lagrangian methods for the simulation of particle-laden flow. Closure is performed in an a priori manner using a reference simulation where all particles in the cloud are traced individually with a point-particle model. Comparison of a first-order model and SPARSE with the reference simulation in one dimension shows that both the stress and the averaging of the carrier-phase velocity on the cloud subscale affect the averaged motion of the particle. A three-dimensional isotropic turbulence computation shows that only one computational parcel is sufficient to accurately trace a cloud of tens of thousands of particles.
机译:提出了拉格朗日粒子云模型,该模型考虑了雷诺平均粒子和湍流应力以及子粒子云尺度的平均载流子相速度对云的平均运动和速度的影响。 SPARSE(亚网格颗粒平均雷诺应力等效)模型基于阻力校正函数的截断泰勒展开和雷诺平均的组合。它减少了在欧拉-拉格朗日方法中追踪粒子云以模拟载有粒子的流动所需的计算包数量。使用参考模拟以先验的方式进行封闭,其中使用点粒子模型分别跟踪云中的所有粒子。一阶模型和SPARSE与一维参考模拟的比较表明,云子尺度上的应力和载流子相速度的平均值都会影响粒子的平均运动。三维各向同性湍流计算表明,只有一个计算包足以准确地跟踪成千上万个粒子的云。

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