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Development and Application of Particle Separation Efficiency Model for a Hydrodynamic Separator with Cumulative Probabilistic Distribution Functions

机译:具有累积概率分布函数的水力分离器颗粒分离效率模型的开发与应用

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The presented study demonstrated that the particle separation efficiency (PSE) for a hydrodynamic separator (HS) as a function of particle size and flow rate could be best modeled using two-parameter cumulative gamma distribution (CGD). The developed PSE model provides continuous 3-D surface response with particle size and flow rate as two input variables. Goodness of fit test and model adequacy check by statistical analysis for model residuals are used to select the appropriate hypothesized distribution functions. It was found that modeled continuous performance curve did closely follow the experimentally measured PSE points across the range of tested flow rates for the tested HS loaded. With the developed PSE model for the HS and frequency distribution of influent hydrologic and granulometric loads, the statistical assessment of the tested HS in terms of particle removal capability, resulting alteration of PSDs across the BMP before discharge to downstream water bodies is provided. In addition, the uncertainty of performance of a particle separation BMP (i.e. statistical distribution of BMP effectiveness from a number of unsteady hydrologic events) is identified.
机译:提出的研究表明,使用两参数累积伽马分布(CGD)可以最好地模拟流体动力分离器(HS)的颗粒分离效率(PSE)与颗粒大小和流速的关系。开发的PSE模型提供了连续的3-D表面响应,其中粒径和流速是两个输入变量。通过对模型残差进行统计分析来进行拟合优度检验和模型充分性检查,以选择适当的假设分布函数。发现在负载的测试HS的整个测试流量范围内,建模的连续性能曲线确实紧随实验测量的PSE点。借助针对HS以及进水水文和颗粒负荷的频率分布的已开发PSE模型,就颗粒清除能力,排放到下游水体之前整个BMP上PSD的变化,对测试的HS进行了统计评估。此外,还确定了颗粒分离BMP的性能不确定性(即,来自许多不稳定水文事件的BMP有效性的统计分布)。

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