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Turbulent velocity distributions and implied trajectory models

机译:湍流速度分布和隐含轨迹模型

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摘要

Well-mixed, first-order Lagrangian stochastic (LS) particle trajectory models are derived from several idealized (toy) turbulent velocity distributions, and their performance is compared against the observations of Project Prairie Grass, i.e., the case of a continuous point source of tracer near the ground, in the horizontally homogeneous and neutrally stratified surface layer. Although in a context of limited information a Gaussian distribution is the preferred choice, and although the Gaussian corresponds to the simplest of this set of LS models (namely, the Langevin equation), models stemming from other velocity distributions give similar, albeit distinguishable, predictions.
机译:混合良好的一阶拉格朗日随机(LS)粒子轨迹模型是从几种理想的(玩具)湍流速度分布中得出的,并且将它们的性能与Project Prairie Grass的观察结果进行了比较,例如,连续点源为示踪剂靠近地面,在水平均匀且中性分层的表层中。尽管在信息有限的情况下,高斯分布是首选,尽管高斯对应于这组LS模型(即Langevin方程)中的最简单模型,但源自其他速度分布的模型给出了相似但可区分的预测。

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