The paper presents the results of the Battle of Postdisaster Response and Restoration (BPDRR) presented in a special session at the first International water distribution systems analysis & computing and control in the water industry (WDSA/CCWI) Joint Conference, held in Kingston, Ontario, Canada, in July 2018. The BPDRR problem focused on how to respond and restore water service after the occurrence of five earthquake scenarios that cause structural damage in a water distribution system. Participants were required to propose a prioritization schedule to fix the damages of each scenario while following restrictions on visibility/nonvisibility of damages. Each team/approach was evaluated against six performance criteria: (1) time without supply for hospital/firefighting, (2) rapidity of recovery, (3) resilience loss, (4) average time of no user service, (5) number of users without service for eight consecutive hours, and (6) water loss. Three main types of approaches were identified from the submissions: (1) general-purpose metaheuristic algorithms, (2) greedy algorithms, and (3) ranking-based prioritizations. All three approaches showed potential to solve the challenge efficiently. The results of the participants showed that for this network, the impact of a large-diameter pipe failure on the network is more significant than several smaller pipes failures. The location of isolation valves and the size of hydraulic segments influenced the resilience of the system during emergencies. On average, the interruptions to water supply (hospitals and firefighting) varied considerably among solutions and emergency scenarios, highlighting the importance of private water storage for emergencies. The effects of damages and repair work were more noticeable during the peak demand periods (morning and noontime) than during the low-flow periods; and tank storage helped to preserve functionality of the network in the first few hours after a simulated event.

On the maintenance task list of each water distribution system (WDS) operator, determination of the order of undertaken repairs seems quite a typical task. Characteristics of damages, their localization, and other factors that influence repair sequencing have a sound impact on the execution of such tasks. In the case of the most complex cases where numerous failures of different types occur at the very same time (i.e., due to earthquakes), there is a long list of selection criteria that have to be analyzed to deliver an objectively logical schedule for repair teams. In this article, authors attempt to find out if it is possible to define pipe rankings in having obtained the best factors for defined objective functions (criteria), making it feasible to deliver judicious repair sequencing. For the purposes of this paper, a survey has been carried out. Its conclusions made it possible to propose a method to create rankings of pipes and evaluate them using a selected multicriteria decision method: preference ranking organization method for enrichment evaluation (PROMETHEE). The work was carried out for five different disaster scenarios that had been supplied by ‘The Battle of Post-Disaster Response and Restoration’ organization committee. Obtained results might be further used to finetune this sequencing method of undertaken repairs, while conclusions could be useful to model similar events in WDS when required. This article is an extended paper based on the conference preprint presented at the 1st International Water Distribution Systems Analysis (WDSA)/International Computing & Control for the Water Industry (CCWI) Joint Conference in July 23–25, 2018 in Kingston, Ontario, Canada.

Paper presents a method of using EPANET solver to support manage water distribution system in Smart City. The main task is to develop the application that allows remote access to the simulation model of the water distribution network developed in the EPANET environment. Application allows to perform both single and cyclic simulations with the specified step of changing the values of the selected process variables. In the paper the architecture of application was shown. The application supports the selection of the best device control algorithm using optimization methods. Optimization procedures are possible with following methods: brute force, SLSQP (Sequential Least SQuares Programming), Modified Powell Method. Article was supplemented by example of using developed computer tool.

Wydawnictwo SIGMA-NOT wydaje czasopisma fachowe informuj?ce swoich czytelnik?w o najnowszych osi?gni?ciach naukowych i nowoczesnych rozwi?zaniach technicznych w Polsce i na ?wiecie, popularyzuje problemy techniczne oraz poszerza wiedz? i kultur? techniczn?.

This study demonstrates the use of the differential evolution method for optimizing multi-source water supply systems. The objective was to identify a water-supply scenario that minimizes the total water-supply costs in multiple sources network. The analysis assumed varying water-production costs at each source, with control implemented through the adjustment of valve settings at the network inlets. For the research, open-source tools such as EPANET, the WNTR library, and Python’s scipy.optimize package, were utilized. The analyses were conducted on two water distribution networks. The first was a simplified network with three water sources, designed to validate the simulation environment and perform initial assessments of the optimization algorithms, whereas the second was a complex model representing a real water distribution network. Analyses were conducted for the latter assuming three, four, five, and six sources. For both networks, multiple pricing scenarios were evaluated to explore how different conditions impact the performance of the algorithm. The results show that near-optimal solutions can be achieved with significantly reduced computation times. The differences in objective function values between the brute force and differential evolution (DE) methods were no greater than 0.2%, while the computation time for DE was substantially shorter. These findings highlight DE scalability, efficiency, and potential for real-world applications, promoting cost-effective and accessible optimization in engineering practice.