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首页> 外文期刊>Journal of hydrologic engineering >Renyi Entropy and Random Walk Hypothesis to Study Suspended Sediment Concentration
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Renyi Entropy and Random Walk Hypothesis to Study Suspended Sediment Concentration

机译:Renyi熵和随机游走假说研究悬浮泥沙浓度

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摘要

Sediment concentration in open channels is fundamental to modeling sediment and pollutant transport. This study employs Renyi entropy for deriving the vertical distribution of suspended sediment concentration in open-channel flow. The derivation maximizes entropy by invoking the principle of maximum entropy, which selects the least-biased probability distribution out of many probability distributions that satisfy a given set of constraints. By considering point source release of sediment particles along with the assumption that the movement of sediment particles follow a nonlinear differential equation, the concentration distribution of suspended sediment is also investigated using a random walk hypothesis. The distribution obtained here is found to be similar to that obtained using entropy. The distribution is evaluated with experimental and field observations and good agreement is observed between computed and measured data. An error analysis is carried out to support the results and the relative root-mean-square error varies from 0.125 to 0.872 for experimental and from 0.141 to 0.510 for field data. Comparison with another entropy-based distribution shows higher accuracy of the proposed distribution.
机译:明渠中的泥沙浓度是模拟泥沙和污染物迁移的基础。本研究利用仁义熵推导明渠水流中悬浮泥沙浓度的垂直分布。该推导通过调用最大熵原理来最大化熵,该原理从满足一组给定约束的许多概率分布中选择最小偏差的概率分布。通过考虑沉积物颗粒的点源释放以及沉积物颗粒的运动遵循非线性微分方程的假设,还使用随机游走假设研究了悬浮沉积物的浓度分布。发现这里获得的分布与使用熵获得的分布相似。通过实验和现场观察评估分布,并在计算和测量数据之间观察到良好的一致性。进行误差分析以支持结果,并且实验的相对均方根误差在0.125到0.872之间,对于现场数据,相对均方根误差在0.141到0.510之间。与另一种基于熵的分布进行比较表明,所提出的分布具有更高的准确性。

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