Abstract In this investigation, the accuracy of the discrete and continuous random walk (DRW, CRW) stochastic models for simulation of fluid (material) point particle, as well as inertial and Brownian particles, was studied. The corresponding dispersion, concentration, and deposition of suspended micro- and nano-particles in turbulent flows were analyzed. First, the DRW model used in the ANSYS-Fluent commercial CFD code for generating instantaneous flow fluctuations in inhomogeneous turbulent flows was evaluated. For this purpose, turbulent flows in a channel were simulated using a Reynolds-averaged Navier–Stokes (RANS) approach in conjunction with the Reynolds Stress Transport turbulence model (RSTM). Then spherical particles with diameters in the range of 30 µm to 10 nm were introduced uniformly in the channel. Under the assumption of one-way coupling, ensembles of particle trajectories for different sizes were generated by solving the particle equation of motion, including the drag and Brownian forces. The DRW stochastic turbulence model of the software was used to include the effects of instantaneous velocity fluctuations on particle motion, and the steady state concentration distribution and deposition velocity of particles of various sizes were evaluated. In addition, the improved CRW model based on the normalized Langevin equation was used in an in-house Matlab code. Comparisons of the predicted results of the DRW model of ANSYS-Fluent with the available experimental data and the DNS simulation results and empirical predictions showed that this model is not able to accurately predict the flow fluctuations seen by the particles in that it leads to unreasonable concentration profiles and time-varying deposition velocities. However, the predictions of the improved CRW model were in good agreement with the experimental data and the DNS results. Possible reasons causing the discrepancies between the DRW predictions and the experimental data were discussed. The improved CRW model was also implemented through user-defined functions into the ANSYS-Fluent code, which resulted in accurate concentration distribution and deposition velocity for different size particles.

中文翻译：

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用于模拟载颗粒湍流的随机行走模型

摘要 在这项研究中，研究了离散和连续随机游走 (DRW, CRW) 随机模型在模拟流体（材料）点粒子以及惯性和布朗粒子时的准确性。分析了湍流中悬浮微粒和纳米颗粒的相应分散、浓度和沉积。首先，评估了在 ANSYS-Fluent 商业 CFD 代码中用于在非均匀湍流中产生瞬时流动波动的 DRW 模型。为此，使用雷诺平均纳维-斯托克斯 (RANS) 方法结合雷诺应力传输湍流模型 (RSTM) 来模拟通道中的湍流。然后将直径在 30 µm 至 10 nm 范围内的球形颗粒均匀地引入通道中。在单向耦合的假设下，通过求解包括阻力和布朗力在内的粒子运动方程，生成了不同尺寸粒子轨迹的集合。利用软件的DRW随机湍流模型，包括瞬时速度波动对粒子运动的影响，对不同粒径粒子的稳态浓度分布和沉积速度进行评价。此外，在内部 Matlab 代码中使用了基于归一化 Langevin 方程的改进 CRW 模型。ANSYS-Fluent的DRW模型的预测结果与已有的实验数据、DNS仿真结果和经验预测的比较表明，该模型无法准确预测颗粒所看到的流动波动，导致不合理的浓度剖面和随时间变化的沉积速度。然而，改进的 CRW 模型的预测与实验数据和 DNS 结果非常一致。讨论了造成 DRW 预测与实验数据差异的可能原因。改进的 CRW 模型还通过用户定义的函数实现到 ANSYS-Fluent 代码中，从而为不同尺寸的颗粒提供准确的浓度分布和沉积速度。