To improve the fidelity of large eddy simulation (LES) of spray jet dispersion, a dynamic subgrid dispersion model is proposed based on the Langevin-type stochastic framework to quantify the effective contribution of the stochastic component of the force as a function of the Stokes number related to the subgrid time scale, which is easily accessed by the LES closure model. The proposed model has two coefficients that require calibration, which were obtained following a rigorous calibration procedure based on forward uncertainty quantification algorithms. The performance of the model is assessed by comparison against a reference direct numerical simulation (DNS) test case. The comparisons for the spray analysis include averages of the number of droplets, mass source term and droplet diameters conditioned on the vapor mass fraction, together with their Eulerian average at different axial locations. The results showed improved prediction of the particle clustering behavior near the nozzle exit observed in the DNS simulations.

中文翻译：

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基于斯托克斯数的大涡模拟随机色散模型改进

为了提高喷雾射流弥散大涡模拟（LES）的保真度，提出了一种基于Langevin型随机框架的动态亚网格弥散模型，以量化力的随机分量作为斯托克斯数函数的有效贡献与子网格时间尺度相关，可以通过 LES 闭合模型轻松访问。所提出的模型有两个需要校准的系数，这些系数是根据前向不确定性量化算法经过严格的校准程序获得的。通过与参考直接数值模拟 (DNS) 测试用例进行比较来评估模型的性能。喷雾分析的比较包括液滴数量的平均值、质量源项和以蒸气质量分数为条件的液滴直径，以及不同轴向位置的欧拉平均值。结果表明，改进了 DNS 模拟中观察到的喷嘴出口附近粒子聚类行为的预测。