A structural subgrid-scale model for relative dispersion in large-eddy simulation of isotropic turbulent flows by coupling kinematic simulation with approximate deconvolution method
A structural subgrid-scale model for relative dispersion in large-eddy simulation of isotropic turbulent flows by coupling kinematic simulation with approximate deconvolution method
复制标题
通过耦合运动学模拟与近似反卷积方法，构建了各向同性湍流大涡模拟中相对色散的结构亚网格尺度模型
DOI：
10.1063/1.5049731
复制
发表时间：
2018-10-01
影响因子：
4.6
通讯作者：
Jin, Guodong
中科院分区：
文献类型：
--
作者：
Zhou, Zhideng;Wang, Shizhao;Jin, Guodong
为了预测各向同性湍流大涡模拟(LES)中流体颗粒的拉格朗日相对弥散，提出了一种近似反卷积(KSAD)混合模型的运动学模拟方法。在该模型中，通过滤光片宽度尺度上的能量通量建立了分辨率尺度和子网格尺度之间的物理联系。由于缺乏亚网格尺度(SGS)湍流结构和SGS模式误差，大涡模拟不能准确预测流体颗粒的两点和多点拉格朗日统计量。为了提高大涡模拟的预报能力，我们使用近似反褶积模型来改善滤波宽度附近的分辨尺度，并通过运动学模拟来恢复亚网格尺度下丢失的速度起伏。为了验证所提出的混合模型，我们将两粒子和四粒子弥散的拉格朗日统计量与直接数值模拟和常规大涡模拟的相应结果进行了比较。结果表明，KSAD混合模型对流体颗粒的拉格朗日统计量的预测有较大的改善。此外，还对波数和方向波向量进行了参数研究，以减少计算量。利用少量的波数模和定向波矢可以得到较好的结果。因此，我们可以在可接受的计算代价下，通过应用KSAD混合模式来改进对大涡模拟中流体颗粒拉格朗日弥散的预测。由AIP出版公司出版。
A kinematic simulation with an approximate deconvolution (KSAD) hybrid model is proposed to predict the Lagrangian relative dispersion of fluid particles in a large eddy simulation (LES) of isotropic turbulent flows. In the model, a physical connection between the resolved and subgrid scales is established through the energy flux rate at the filter width scale. Due to the lack of subgrid-scale (SGS) turbulent structures and SGS model errors, the LES cannot accurately predict the two-and multi-point Lagrangian statistics of the fluid particles. To improve the predictive capability of the LES, we use an approximate deconvolution model to improve the resolved scales near the filter width and a kinematic simulation to recover the missing velocity fluctuations beneath the subgrid scales. To validate the proposed hybrid model, we compare the Lagrangian statistics of two-and four-particle dispersion with the corresponding results from the direct numerical simulation and the conventional LES. It is found that a significant improvement in the prediction of the Lagrangian statistics of fluid particles is achieved through the KSAD hybrid model. Furthermore, a parametric study regarding the wavenumbers and orientation wavevectors is conducted to reduce the computational cost. Good results can be obtained using a small number of wavenumber modes and orientation wavevectors. Thus, we can improve the prediction of the Lagrangian dispersion of fluid particles in the LES by applying the KSAD hybrid model at an acceptable computational cost. Published by AIP Publishing.