This work presents fluid flow and particle trajectory simulation studies to determine the aspiration efficiency of a horizontally oriented occupational air sampler using computational fluid dynamics (CFD). Grid adaption and manual scaling of the grids were applied to two sampler prototypes based on a 37-mm cassette. The standard k-ε model was used to simulate the turbulent air flow and a second order streamline-upwind discretization scheme was used to stabilize convective terms of the Navier-Stokes equations. Successively scaled grids for each configuration were created manually and by means of grid adaption using the velocity gradient in the main flow direction. Solutions were verified to assess iterative convergence, grid independence and monotonic convergence. Particle aspiration efficiencies determined for both prototype samplers were undistinguishable, indicating that the porous filter does not play a noticeable role in particle aspiration. Results conclude that grid adaption is a powerful tool that allows to refine specific regions that require lots of detail and therefore better resolve flow detail. It was verified that adaptive grids provided a higher number of locations with monotonic convergence than the manual grids and required the least computational effort.

中文翻译：

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使用手动缩放和自适应网格的职业空气采样器对粒子吸收的三维计算流体动力学建模

这项工作提出了流体流动和粒子轨迹模拟研究，以确定使用计算流体动力学 (CFD) 的水平定向职业空气采样器的抽吸效率。网格自适应和手动缩放网格应用于基于 37 毫米暗盒的两个采样器原型。标准 k-ε 模型用于模拟湍流气流，二阶流线-迎风离散化方案用于稳定 Navier-Stokes 方程的对流项。每个配置的连续缩放网格是手动创建的，并且通过使用主要流动方向上的速度梯度的网格自适应来创建。验证解决方案以评估迭代收敛、网格独立性和单调收敛。确定的两个原型采样器的颗粒吸入效率无法区分，表明多孔过滤器在颗粒吸入中没有发挥显着的作用。结果得出结论，网格自适应是一种强大的工具，可以细化需要大量细节的特定区域，从而更好地解析流细节。经验证，自适应网格比手动网格提供了更多的单调收敛位置，并且需要最少的计算工作。