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Observations and Modeling of Heavy Particle Deposition in a Windbreak Flow

机译:防风流中重颗粒沉积的观测与建模

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This paper presents new observations of deposition of heavy particles (glass beads of gravitational settling velocity 8.7 cm s~(-1)) within an undisturbed flow and within a flow disturbed by a porous windbreak fence. These data are then used to diagnose the capability of a Lagrangian stochastic (LS) particle trajectory model, which simulates heavy particle dispersion. The model is based on existing parameterizations and is coupled to a wind model based on a Reynolds stress turbulence closure that provides computed fields of wind statistics. The deposition rates, as simulated by the model, match the observation within E = 30% of accuracy, with E being the root-mean-square error normalized by the peak value on the deposition swath. These results suggest that the LS model handles properly the heterogeneities of the flow and that the heuristic adjustments made to account for the inertia of heavy particles are useful approximations. The model consequently proves to be a valuable tool to investigate thepatterns of dispersion about an obstacle.
机译:本文提出了新的观测结果:在不受扰动的流动和受多孔防风栅栏扰动的流动中,重粒子(重力沉降速度为8.7 cm s〜(-1)的玻璃珠)的沉积。然后,这些数据将用于诊断拉格朗日随机(LS)粒子轨迹模型的能力,该模型可模拟重粒子的弥散。该模型基于现有的参数设置,并耦合到基于雷诺应力湍流闭合的风模型,该闭合模型提供了风的统计信息。该模型模拟的沉积速率与E = 30%的准确度范围内的观测值相符,其中E是通过沉积条带上的峰值归一化的均方根误差。这些结果表明,LS模型可以正确处理流的非均质性,并且为考虑重粒子的惯性而进行的启发式调整是有用的近似值。因此,该模型被证明是研究障碍物分散模式的有价值的工具。

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