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Utilizing Hydraulic Model Based Optimization to Determine Prioritized Solutions to Accommodate Future Growth in Mill Creek Watershed

机译:利用基于水力模型的优化来确定优先解决方案,以适应Mill Creek流域的未来增长

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Johnson County Wastewater (JCW), located on the Kansas side of Kansas City, first applied genetical algorithm (GA) optimization in 2007. The pilot project for the Turkey Creek Basin was one of the first ever applications of this the technology for collection systems. The technology evolved significantly in the 10-years since it was first trialled by JCW. This paper summarizes key technology advancements and discusses how is was applied by JCW to the Mill Creek Watershed in 2017. The Mill Creek optimization utilizes extensive inflow and infiltration (I/I) pilot project results obtained by JCW to determine the cost-effective balance between conveance, storage, treatment and I/I reduction alternatives using formal optimization software, Optimizer WCS (product of Optimatics). Scenarios and sensitivity analyses were performed to determine how key planning assumptions affect the optimization results. Prioritization is applied using the optimization model to determine the sequence of project implentation that maximizes return on investment with respect to overflow reduction.
机译:位于堪萨斯城堪萨斯州一侧的约翰逊县废水(JCW)于2007年首次应用遗传算法(GA)优化。土耳其河盆地的试点项目是该技术首次应用于收集系统。自从JCW首次试用以来,该技术在10年中有了长足的发展。本文总结了关键技术的进步,并讨论了JCW在2017年如何将其应用于Mill Creek流域。Mill Creek优化利用JCW获得的大量入流和入渗(I / I)试点项目结果来确定两者之间的成本效益平衡。使用正式的优化软件Optimizer WCS(Optimatics的产品),可以实现轻巧的存储,存储,处理和I / I减少方案。进行了方案和敏感性分析,以确定关键的计划假设如何影响优化结果。使用优化模型应用优先级来确定项目执行的顺序,以最大程度减少溢出方面的投资回报。

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