Constant-coefficient spatial gradient models for the sub-grid scale closure in large-eddy simulation of turbulence
Constant-coefficient spatial gradient models for the sub-grid scale closure in large-eddy simulation of turbulence
复制标题
湍流大涡模拟中亚网格尺度闭合的恒系数空间梯度模型
DOI：
10.1063/5.0101356
复制
发表时间：
2022-08
影响因子：
4.6
通讯作者：
Jianchun Wang
中科院分区：
文献类型：
--
作者：
Yunpeng Wang;Zelong Yuan;Xiaoning Wang;Jianchun Wang
提出了湍流大涡模拟中亚网格尺度封闭的常系数空间梯度模型(SGM)。通过使用局部高阶梯度扩展相邻的一阶梯度，或者通过使用空间模板位置之间的一阶值直接离散局部高阶梯度来确定模型系数。先验检验表明，SGM模型的相关系数可大于0.97，接近于基于机器学习的模型。在后验检验中，对受迫不可压缩均匀各向同性湍流(HIT)和弱可压缩湍流混合层(TML)分别采用不同的SGS模型。通过对包括速度谱、应变率概率密度函数和速度增量在内的流动统计量的预测，全面检验了SGM模型的性能。为了评价大涡模拟的时空性能，还研究了湍流动能的演变、涡量场的瞬时结构和Q判据。与传统的Smagorinsky模型(DSM)、动态混合模型(DMM)和隐式大涡模拟(ILES)模型相比，SGM模型的预测结果一致更令人满意，而其计算量与传统模型相近。对于弱可压缩TML，当初始扰动场的长度尺度大于滤波片宽度时，大多数大涡模拟效果较好，为湍流混合层大涡模拟提供了有益的指导。
Constant-coefficient spatial gradient models (SGM) are proposed for the sub-grid scale (SGS) closure in large-eddy simulation (LES) of turbulence. The model coefficients are determined either by expanding the neighboring first-order gradients using the local higher-order gradient, or by directly discretizing the local higher-order gradients using first-order values among spatial stencil locations. The a priori tests show that the SGM model can have a correlation coefficient larger than 0.97, which is close to the machine-learning based model. In the a posteriori tests, the LESs with different SGS models are performed for the forced incompressible homogeneous isotropic turbulence (HIT) and weakly compressible turbulent mixing layer (TML). The performance of SGM model is comprehensively examined through the prediction of the flow statistics including the velocity spectrum, the probability density functions (PDFs) of the strain rate and velocity increments. The evolution of turbulent kinetic energy, the instantaneous structures of the vorticity field and the Q-criterion are also examined to evaluate the spatial temporal performances of the LES. The predictions of the SGM model are consistently more satisfying compared to the traditional models, including the dynamic Smagorinsky model (DSM), the dynamic mixed model (DMM) and implicit-LES (ILES) while its computational cost is similar to traditional models. For the weakly compressible TML, most LES perform better when the length scale of the initial perturbation field is larger than the filter width, providing a useful guidance for LES of turbulent mixing layers.