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Improved Rigid Water Column Formulation for Simulating Slow Transients and Controlled Operations

机译:改进的硬水塔公式,用于模拟慢速瞬态和受控操作

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Rigid water column (RWC) models simulate the unsteady-incompressible hydraulics of pressurized pipe networks. They conceptually lie between water hammer and quasi-steady models, yet despite their intrinsic strengths, existing RWC formulations suffer efficiency-, stability-, and interpretation-related challenges; thus, they are typically overlooked as a modeling alternative. To address the aforementioned limitations, this article presents the RWC global gradient algorithm (GGA), a novel formulation for pipe networks that has greater efficiency and overcomes the numerical challenges. The RWC GGA extends the generalized GGA (G-GGA) to consider inertial effects in addition to variable-area tanks and mixed (i.e., demand and pressure-dependent) outflows. Two pipe networks of simple and moderate complexity are used to compare the new approach against two other RWC algorithms, the G-GGA, and a water hammer model: the current work is shown to have improved stability and efficiency relative to previous work. The RWC GGA is also found to have a computational cost only slightly greater than that of the G-GGA for the same time-step size. Overall, this work highlights the practical utility of RWC models to simulate slow transient events and controlled operations.
机译:刚性水塔(RWC)模型可模拟加压管网的非稳态不可压缩水力学。它们在概念上介于水锤模型和准稳态模型之间,但是尽管具有内在优势,现有的RWC公式仍面临效率,稳定性和解释方面的挑战。因此,它们通常被视为建模的替代方案。为了解决上述限制,本文提出了RWC全局梯度算法(GGA),这是一种用于管网的新颖公式,具有更高的效率并克服了数值上的挑战。 RWC GGA扩展了广义GGA(G-GGA),除了可变面积的储罐和混合(即与需求和压力有关)流出之外,还考虑了惯性效应。使用两个简单和中度复杂度的管网将新方法与其他两个RWC算法G-GGA和水锤模型进行比较:相对于以前的工作,当前的工作已显示出更高的稳定性和效率。对于相同的时间步长,还发现RWC GGA的计算成本仅略高于G-GGA。总的来说,这项工作突出了RWC模型在模拟慢速瞬态事件和受控操作方面的实用性。

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