Collaborative Research: Joint Control of Hydraulics and Water Quality Dynamics in Drinking Water Networks

饮用水离开水处理设施后，通过复杂的管道网络输送给消费者。最近的研究表明，经过处理的饮用水在从处理厂到消费者水龙头的过程中质量恶化;这对公共卫生有重大影响。在有限的预算下运营，水务公司采用不同程度的水质监测，这些监测旨在遵守法规，但不适合快速检测和缓解污染事件。此外，公用事业通常缺乏有针对性的实时控制策略，并且通常通过发布公用事业范围的指令（例如，“烧开水”或“不食用”的饮料）。这种污水处理厂具有重大的社会经济影响，而且通常在改善水质方面进展缓慢。与此相反，该项目通过控制液压泵、阀门和消毒剂加药站来应对污染事件，为城市供水网络的实时水质管理创造了新方法。为此，本研究利用水传感技术的最新进展，同时通过环境科学，优化，网络控制和水生化学的跨学科研究来研究控制算法。这项研究能够实时监测和控制水力学和水质，使水务公司采取应对污染事件的策略，并扩大在UT圣安东尼奥，UT奥斯汀和伊利诺伊大学芝加哥的研究和教育中代表性不足的群体的参与。该项目提出了一种新的数学框架，将控制水流和压力的水力方程与描述消毒剂残留物的运输和衰减的动态水质模型耦合在一起，作为饮用水分配网络中污染事件检测的代理。由此产生的框架忠实地描述了网络的正常条件下的操作和污染事件。该框架还可以开发可扩展的优化算法，这些算法可以实时实现对泵、阀门和消毒剂增压站的控制，从而确保符合水质标准。该算法旨在处理各种水系统应用，如流量调制，污染物入侵事件的响应和恢复，以及可靠的网络范围内的消毒。该理论是在现实的水网络模型上进行评估的，此外还有来自固定和移动的传感器的数据，这些传感器从现实的水系统中收集水力和水质数据。该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持的。

After leaving water treatment facilities, drinking water is delivered to consumers through an intricate network of pipes. Recent studies have demonstrated that the quality of treated drinking water deteriorates during the journey from treatment plants to consumers’ taps; this has significant implications for public health. Operating under limited budgets, water utilities adopt different degrees of water quality monitoring that are geared towards regulatory compliance but are unbefitting for rapid detection and mitigation of contamination events. Furthermore, utilities typically lack targeted, real-time control strategies and often respond to contamination events by issuing utility-wide advisories (e.g., “boil water” or “do not consume” advisories). Such advisories have significant socio-economic impacts and are typically slow in improving water quality. In contrast to this, this project creates new methods for real-time water quality management in urban water networks by controlling hydraulic pumps, valves, and disinfectant dosing stations in response to contamination events. To this end, this research harnesses recent advances in water sensing technologies while investigating control algorithms through interdisciplinary research from environmental science, optimization, network control, and aquatic chemistry. This research enables real-time monitoring and control of hydraulics and water quality, allows water utilities to adopt strategies in response to contamination events, and broadens participation of underrepresented groups in research and education at UT San Antonio, UT Austin and the University of Illinois at Chicago. This project puts forth a novel mathematical framework that couples the hydraulic equations governing water flow and pressure with dynamic water quality models depicting the transport and decay of disinfectant residuals, which act as a proxy for contamination event detection in drinking water distribution networks. The resulting framework faithfully describes the network operation under regular conditions and contamination events. This framework also enables the development of scalable optimization algorithms that are amenable to real-time implementation for control of pumps, valves, and disinfectant booster stations, thereby ensuring compliance with water quality standards. The algorithms are designed to deal with a variety of water system applications such as flow modulation, response and recovery from contaminant intrusion events, and reliable network-wide disinfection. The theory is evaluated on realistic water network models in addition to data from fixed and mobile sensors that collect hydraulic and water quality data from a real-life water system.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.