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Modelling of distribution of aerosol emission with account of buildings and structures of NPPs

机译:空气溶解排放分布与核磁共振的建筑物和结构建模

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In the lack of experimental data and due to the rapid development of numerical modelling and computer hardware, computational fluid dynamics (CFD) is widely used to study wind field and contaminant transport around buildings. The ability to predict quantitative values for these processes is not so clear. CFD simulations work under neutral atmospheric conditions and are validated by the Gauss model. The Gaussian model is a mathematical distribution of the concentration of contaminants from NPP ventilation pipes. It is the most recommended model by the IAEA and most widely used because 1) it gives results consistent with experimental data, 2) it is quite easy to use, and 3) it is consistent with the aleatory nature of turbulence. Reynolds-averaged Navier-Stokes equations is the most widely used method in turbulent flow modeling and simulation. In this paper, the prediction of flow accuracy and propagation around buildings with a stack was examined using k-e model. The numerical results were compared to Gauss model results. Contaminant dispersion was well predicted with k-e model. It was also confirmed that the concentrations predicted by the CFD models were more diffused than those of the Gauss model and that the results depend on the position of the obstacles.
机译:在缺乏实验数据并且由于数值建模和计算机硬件的快速发展,计算流体动力学(CFD)被广泛用于研究风场和建筑物周围的污染物运输。预测这些过程的定量值的能力并不明确。 CFD模拟在中性大气条件下工作,并通过高斯模型进行验证。高斯模型是NPP通风管污染物浓度的数学分布。它是IAEA最推荐的模型,最广泛使用,因为1)它给出了与实验数据一致的结果,2)非常易于使用,3)它与湍流的溶液性质一致。 Reynolds-Iveriged Navier-Stokes方程是湍流流量建模和仿真中最广泛使用的方法。在本文中,使用K-E模型检查了与堆栈的建筑物周围的流量精度和传播的预测。将数值结果与高斯模型结果进行比较。用K-E模型预测污染物分散体。还证实,CFD模型预测的浓度比高斯模型更扩散,结果取决于障碍物的位置。

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