The study presents a novel ANN-CFD model for simulating flow in a vortex mixer (an unbaffled vessel stirred by a magnetic stirrer). Large eddy simulations (LES) are performed to simulate flow and turbulence considering presence of both air and liquid phases. The flow fields in air and liquid phases are coupled by applying suitable boundary conditions at the air–liquid interface represented by the vortex. The shape of the vortex is built-in in the computational domain and obtained by using an artificial neural network (ANN) model trained and validated with the data obtained from experiments carried out to capture the vortex shape under different parametric conditions. ANN-CFD model is validated with PIV data reported in literature. The ANN-CFD model reduces the computational time significantly by obviating the need of performing computationally very intensive interface tracking simulations. The model is used to understand hydrodynamics and turbulence characteristics of flow in the vortex mixer.

该研究提出了一种新颖的 ANN-CFD 模型，用于模拟涡流混合器（由磁力搅拌器搅拌的无挡板容器）中的流动。考虑到空气和液相的存在，执行大涡模拟 (LES) 以模拟流动和湍流。通过在由涡流表示的气液界面处应用合适的边界条件，可以耦合气液相中的流场。涡旋的形状内置在计算域中，并通过使用人工神经网络 (ANN) 模型获得，该模型使用从为捕获不同参数条件下的涡旋形状而进行的实验中获得的数据进行训练和验证。ANN-CFD 模型通过文献报道的 PIV 数据进行验证。ANN-CFD 模型消除了执行计算量非常大的界面跟踪模拟的需要，从而显着减少了计算时间。该模型用于了解涡流混合器中流动的流体动力学和湍流特性。