34 research outputs found
Better Understanding of the Capacity of Pressure Sensor Systems to Detect Pipe Burst within Water Distribution Networks
No full textAbstract not availableZhexian Qi, Feifei Zheng, Danlu Guo, Holger R. Maier, Tuqiao Zhang,
Tingchao Yu, and Yu Shao
Impact of main pipe flow velocity on leakage and intrusion flow: an experimental study
No full textThe classic orifice equation is commonly used to calculate the leakage and intrusion rate for pressurized pipelines with cracks on the pipe wall. The conventional orifice equation does not consider the effect of the flow velocity in the main pipe, and there is a lack of studies on this matter. For this technical note, the influence of the main pipe flow velocity on the outflow and inflow through a crack on the pipe wall was studied in the laboratory. The experimental results show that the impact of the main pipe flow velocity can be significant. When the pressure difference across the orifice was constant, with the increase of the main pipe flow velocity, the outflow velocity increased, but the contraction area of the jet and the outflow discharge coefficient decreased. By comparing orifices with different shapes, it was found that the discharge from the circumferential crack was most sensitive to the main pipe flow velocity. In addition, the main pipe flow promoted the orifice inflow. When the pressure difference across the orifice was constant, with the increase of the main pipe flow velocity, the inflow discharge coefficient increased, which is the opposite pattern to that of the orifice outflow.Yu Shao, Tian Yao, Jinzhe Gong, Jinjie Liu, Tuqiao Zhang, and Tingchao Y
Leakage Control and Energy Consumption Optimization in the Water Distribution Network Based on Joint Scheduling of Pumps and Valves
No full textApart from water quality, leakage control and energy consumption management are the most concerning challenges for water treatment plants (WTPs). The joint scheduling of pumps and pressure reducing valves (PRVs) in the water distribution network can reduce excessive pressure and distribute pressure more evenly, which achieves comprehensive reduction of leakages and energy consumption. Taking into account the main shortcomings of the commonly used methods, such as scheduling pumps or PRVs separately, or optimizing PRV settings when their position is given, etc., this paper has taken the PRV (position and setting) and the working status of variable speed pumps (VSPs) as decision variables and the cost savings contributed by leakage reduction and energy consumption savings as the objective function, which maximized the economic benefits brought by PRV and/or VSP scheduling. A genetic algorithm (GA) was used to optimize the solution under multiple working conditions. The performance of three control strategies (PRV-only scheduling, VSP-only scheduling, and joint scheduling of PRVs and VSPs) are compared to each other based on a small network. Joint scheduling has achieved the best economic benefits in reducing the gross cost (contributed by leakage and energy consumption) of the three control strategies, which results in a leakage reduction of 33.4%, an energy consumption reduction of 25.4%, and a total cost reduction of 33.1%, when compared to the original network, and saving about 1148 m 3 water (7% of the original consumption) and 722 kWh electric energy (25.4% of the original consumption) per day
Explainable graph neural network for real-time demand states forecasting in water distribution system
No full textEfficient real-time nodal demand forecasting in water distribution systems is essential for a reliable and resilient water supply. Given the efficiency of the data-driven approach and the intricate node-line structure of water networks, graph-based machine learning methods offer a promising approach. However, the scarcity of real-time flow acquisition devices limits the ability to directly forecast timely demand. Pressure sensors provide a more practical alternative. Thus, this study proposes a novel attention-augmented gated graph neural network (AGN) for real-time demand forecasting from a pressure perspective. By integrating attention mechanisms, the AGN overcomes limitations of convolution-based graph neural networks, such as capturing long-range dependencies and dynamic node interactions, leading to enhanced performance on real-world modeling problems. This model is formulated for real and sensitive contexts where, in addition to being accurate, the predictions must also be understandable by human operators. Thus, model-level explanations are then introduced in our explainable framework. The proposed AGN outperforms benchmark methods in both spatiotemporal accuracy and long-term forecasting effectiveness, while simultaneously delivering interpretable insights into the demand forecasting process. The novel approach based on the fusion of forecasting and explainability in a single framework enables the creation of powerful and reliable systems suitable for real-world issues and challenges
Multi-Stage Burst Localization Based on Spatio-Temporal Information Analysis for District Metered Areas in Water Distribution Networks
No full textBurst events in Water Distribution Networks (WDNs) pose a significant threat to the safety of water supply, leading people to focus on efficient methods for burst localization and prompt repair. This paper proposes a multi-stage burst localization method, which includes preliminary region determination and precise localization analysis. Based on the hydraulic model and spatio-temporal information, the effective sensor sequences and monitoring areas of the nodes are determined. In the first stage, the preliminary burst region is determined based on the monitoring region of sensors and the alarm sensors. In the second stage, localization metrics are used to analyze the dissimilarity degree between burst data from the hydraulic model and the monitoring data from the effective sensors at each node. This analysis helps identify candidate burst nodes and determine their localization priorities. The localization model is tested on the C-Town network to obtain comparative results. The method effectively reduces the burst region, minimizes the search region, and significantly improves the efficiency of burst localization. For precise localization, it accurately localizes the burst event by prioritizing the possibilities of the burst location
Association between spicy food consumption and lipid profiles in adults: a nationwide population-based study
No full textCVD remains the leading cause of mortality worldwide, with abnormal lipid metabolism as a major risk factor. The aim of this study was to investigate associations between spicy food consumption and serum lipids in Chinese adults. Data were extracted from the 2009 phase of the China Health and Nutrition Survey, consisting of 6774 apparently healthy Chinese adults aged 18-65 years. The frequency of consumption and degree of pungency of spicy food were self-reported, and regular spicy food consumption was assessed using three consecutive 24-h recalls. Total cholesterol, TAG, LDL-cholesterol and HDL-cholesterol in fasting serum were measured. Multilevel mixed-effects models were constructed to estimate associations between spicy food consumption and serum lipid profiles. The results showed that the frequency and the average amount of spicy food intake were both inversely associated with LDL-cholesterol and LDL-cholesterol: HDL-cholesterol ratio (all Pfor trend < 0.05) after adjustment for potential confounders and cluster effects. HDL-cholesterol in participants who usually consumed spicy food (>= 5 times/week) and who consumed spicy food perceived as moderate in pungency were significantly higher than those who did not (both P < 0.01). The frequency and the average amount of spicy food intake and the degree of pungency in spicy food were positively associated with TAG (all Pfor trend < 0.05). Spicy food consumption was inversely associated with serum cholesterol and positively associated with serum TAG, and additional studies are needed to confirm the findings as well as to elucidate the potential roles of spicy food consumption in lipid metabolism.SCI(E)ARTICLE2144-15311
Comparative Analysis on the DMA Partitioning Methods Whether Trunk Mains Participated
No full textIn recent years, the District Metered Area (DMA) of water distribution networks (WDNs) has become a major development trend in the water leakage control area. It has significant value in the active leakage control and pressure management of WDNs. This study comments on two DMA partitioning methods (Scheme A and B, previously introduced in another paper) and compares three aspects of their respective performances to elucidate their respective strengths and weaknesses. Scheme A partitions all the network nodes, whereas Scheme B only partitions the remaining network nodes, except the trunk mains. Whether the trunk mains participated in the partitioning process is the key distinction between the two approaches. There is little relevant research that compares and analyzes the effects of the above two methods. This paper applies these two types of partitioning methods to a case network. The respective performances in three aspects, namely economy, water quality, and leakage control, were evaluated and compared. For economy, Scheme A is more economical than Scheme B, saving about 15.34%. For water quality, Scheme B is the best partitioning method because it reduces water age better than Scheme A does. For leakage control, Scheme B has a drop of 19.46%, which is better than Scheme A (a decline of 15.12%) in comparison to the initial leakage
Treatment of Aqueous Bromate by Superparamagnetic BiOCl-Mediated Advanced Reduction Process
No full textBromate ( BrO 3 − ) contamination in drinking water is a growing concern. Advanced reduction processes (ARPs) are reportedly promising in relieving this concern. In this work, UV/superparamagnetic BiOCl (BiOCl loaded onto superparamagnetic hydroxyapatite) assisted with small molecule carboxylic acid (formate, citrate, and acetate), a carboxyl anion radical ( CO 2 • − )-based ARP, was proposed to eliminate aqueous BrO 3 − . Formate and citrate were found to be ideal CO 2 • − precursor, and the latter was found to be safe for practical use. BrO 3 − (10 μg·L−1, WHO guideline for drinking water) can be completely degraded within 3 min under oxygen-free conditions. In this process, BrO 3 − degradation was realized by the reduction of CO 2 • − (major role) and formyloxyl radical (minor role) in bulk solution. The formation mechanism of radicals and the transformation pathway of BrO 3 − were proposed based on data on electron paramagnetic resonance monitoring, competitive kinetics, and degradation product analysis. The process provided a sustainable decontamination performance (<5% deterioration for 10 cycles) and appeared to be more resistant to common electron acceptors (O2, NO 3 − , and Fe3+) than hydrated electron based-ARPs. Phosphate based-superparamagnetic hydroxyapatite, used to support BiOCl in this work, was believed to be applicable for resolving the recycling problem of other metal-containing catalyst
