论文标题
Lagrangian随机模型，用于湍流中惯性球形颗粒的方向：一种有效的CFD方法的数值方法
Lagrangian stochastic model for the orientation of inertialess spheroidal particles in turbulent flows: an efficient numerical method for CFD approach
论文作者
论文摘要
在这项工作中，我们提出了一个模型，用于悬浮在湍流中的惯性球形颗粒的方向。该模型由jeffery方程的随机版本组成，该版本可以包含在悬浮在流中的粒子的统计拉格朗日描述中。它与湍流模型相兼容，并相干，这些模型被广泛用于CFD代码中，以模拟实用大规模应用中流场的模拟。在这种情况下，我们根据分裂方案算法提出和分析数值方案，该方案将方向动力学分解为其主要贡献：拉伸和旋转。我们在开源CFD软件中详细介绍其实现。我们分析了整体方案和每个子部分的弱和强收敛。随后，分裂技术会产生高效的杂种算法耦合纯概率和确定性数值方案。实施了各种数值实验，并将结果与模型的分析预测进行了比较，以评估算法效率和准确性。
In this work, we propose a model for the orientation of inertialess spheroidal particles suspended in turbulent flows. This model consists in a stochastic version of the Jeffery equation that can be included in a statistical Lagrangian description of particles suspended in a flow. It is compatible and coherent with turbulence models that are widely used in CFD codes for the simulation of the flow field in practical large-scale applications. In this context, we propose and analyze a numerical scheme based on a splitting scheme algorithm that decouples the orientation dynamics into its main contributions: stretching and rotation. We detail its implementation in an open-source CFD software. We analyze the weak and strong convergence of both the global scheme and of each sub-part. Subsequently, the splitting technique yields to a highly efficient hybrid algorithm coupling pure probabilistic and deterministic numerical schemes. Various numerical experiments were implemented and the results were compared with analytical predictions of the model to assess the algorithm efficiency and accuracy.
