As the size of water distribution network (WDN) models continues to grow, developing and applying real-time models or digital twins to simulate hydraulic behaviors in large-scale WDNs is becoming increasingly challenging. The long response time incurred when performing multiple hydraulic simulations in large-scale WDNs can no longer meet the current requirements for the efficient and real-time application of WDN models. To address this issue, there is a rising interest in accelerating hydraulic calculations in WDN models by integrating new model structures with abundant computational resources and mature parallel computing frameworks. This paper presents a novel and efficient framework for steady-state hydraulic calculations, comprising a joint topology-calculation decomposition method that decomposes the hydraulic calculation process and a high-performance decomposed gradient algorithm that integrates with parallel computation. Tests in four WDNs of different sizes with 8 to 85,118 nodes demonstrate that the framework maintains high calculation accuracy consistent with EPANET and can reduce calculation time by up to 51.93 % compared to EPANET in the largest WDN model. Further investigation found that factors affecting the acceleration include the decomposition level, consistency of sub-model sizes and sub-model structures. The framework aims to help develop rapid-responding models for large-scale WDNs and improve their efficiency in integrating multiple application algorithms, thereby supporting the water supply industry in achieving more adaptive and intelligent management of large-scale WDNs.

中文翻译：

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用于加速大型配水管网中的水力模拟的深层次分解模型


随着配水管网 （WDN） 模型规模的不断扩大，开发和应用实时模型或数字孪生来模拟大规模 WDN 中的水力行为变得越来越具有挑战性。在大型 WDN 中执行多个水力模拟时产生的较长响应时间已无法满足当前对 WDN 模型的高效和实时应用的要求。为了解决这个问题，通过将新的模型结构与丰富的计算资源和成熟的并行计算框架集成，加速 WDN 模型中的水力计算越来越受到关注。该文提出了一种新颖高效的稳态水力计算框架，包括分解水力计算过程的联合拓扑-计算分解方法和与并行计算集成的高性能分解梯度算法。在四个不同大小的 WDN（8 到 85,118 个节点）中的测试表明，该框架保持了与 EPANET 一致的高计算精度，与最大 WDN 模型中的 EPANET 相比，可以将计算时间缩短高达 51.93%。进一步研究发现，影响加速度的因素包括分解水平、子模型大小的一致性和子模型结构。该框架旨在帮助开发大规模 WDN 的快速响应模型，提高其集成多种应用算法的效率，从而支持供水行业实现对大规模 WDN 的更具适应性和智能性的管理。