scholarly journals GPU Acceleration of Hydraulic Transient Simulations of Large-Scale Water Supply Systems

2018 ◽  
Vol 9 (1) ◽  
pp. 91
Author(s):  
Wanwan Meng ◽  
Yongguang Cheng ◽  
Jiayang Wu ◽  
Zhiyan Yang ◽  
Yunxian Zhu ◽  
...  
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Large Scale ◽  
Parallel Implementation ◽  
Water Supply Systems ◽  
Processing Unit ◽  
Long Distance ◽  
Hydraulic Transients ◽  
Practical Applications

Simulating hydraulic transients in ultra-long water (oil, gas) transmission or large-scale distribution systems are time-consuming, and exploring ways to improve the simulation efficiency is an essential research direction. The parallel implementation of the method of characteristics (MOC) on graphics processing unit (GPU) chips is a promising approach for accelerating the simulations, because GPU has a great parallelization ability for massive but simple computations, and the explicit and local features of MOC meet the features of GPU quite well. In this paper, we propose and verify a GPU implementation of MOC on a single chip for more efficient simulations of hydraulic transients. Details of GPU-MOC parallel strategies are introduced, and the accuracy and efficiency of the proposed method are verified by simulating the benchmark single pipe water hammer problem. The transient processes of a large scale water distribution system and a long-distance water transmission system are simulated to investigate the computing capability of the proposed method. The results show that GPU-MOC method can achieve significant performance gains, and the speedup ratios are up to hundreds compared to the traditional method. This preliminary work demonstrates that GPU-MOC parallel computing has great prospects in practical applications with large computing load.

scholarly journals Burst Detection in Water Distribution Systems: The Issue of Dataset Collection

2020 ◽  
Vol 10 (22) ◽  
pp. 8219
Author(s):  
Andrea Menapace ◽  
Ariele Zanfei ◽  
Manuel Felicetti ◽  
Diego Avesani ◽  
Maurizio Righetti ◽  
...  
Keyword(s):  
Water Supply ◽  
Water Consumption ◽  
Distribution System ◽  
Smart Grids ◽  
Distribution Systems ◽  
Water Distribution ◽  
Stochastic Modelling ◽  
Water Supply Systems ◽  
Consumption Data ◽  
Supply Systems

Developing data-driven models for bursts detection is currently a demanding challenge for efficient and sustainable management of water supply systems. The main limit in the progress of these models lies in the large amount of accurate data required. The aim is to present a methodology for the generation of reliable data, which are fundamental to train anomaly detection models and set alarms. Thus, the results of the proposed methodology is to provide suitable water consumption data. The presented procedure consists of stochastic modelling of water request and hydraulic pipes bursts simulation to yield suitable synthetic time series of flow rates, for instance, inlet flows of district metered areas and small water supply systems. The water request is obtained through the superimposition of different components, such as the daily, the weekly, and the yearly trends jointly with a random normal distributed component based on the consumption mean and variance, and the number of users aggregation. The resulting request is implemented into the hydraulic model of the distribution system, also embedding background leaks and bursts using a pressure-driven approach with both concentrated and distributed demand schemes. This work seeks to close the gap in the field of synthetic generation of drinking water consumption data, by establishing a proper dedicated methodology that aims to support future water smart grids.

scholarly journals E-Metering and Fault Detection in Smart Water Distribution Systems using Wireless Network

2019 ◽  
Vol 8 (11) ◽  
pp. 634-639
Keyword(s):  
Real Time ◽  
Sensor Network ◽  
Network Model ◽  
Rural Areas ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Large Scale ◽  
Water Distribution System ◽  
Smart Water

Water distribution system is a network that supplies water to all the consumers through different means. Proper means of providing water to houses without compromising in quantity and quality is always a challenge. As it is a huge network keeping track of the utilization is difficult for the utility. Hence through this project we come up with a solution to solve this issue. Current technologies like Low Power Wide Area Networks, LoRa and sensor deployment techniques have been in research and were also tested in few rural areas but issues due to hardware deployment and large scale real time implementation was a challenge hence through this system we aim to create and simulate a real time scenario to test a sensor network model that could be implemented in large scale further. This project aims in building a wireless sensor network model for a smart water distribution system. In this system there is bidirectional communication between the consumer and the utility. Each house has a meter through which the amount of water consumed is sent to the utility board. The data has two fields containing the house ID and the data (water consumed); it is being sent to the data collection unit (DCU) which in-turn sends it to the central server so that the consumption is monitored in real time. All this is simulated using NETSIM and MATLAB

scholarly journals Assessing the impact of working pressure on water meter registration

2021 ◽  
Author(s):  
Isaac G. Musaazi ◽  
Jotham I. Sempewo ◽  
Mohammed Babu ◽  
Nicholas Kiggundu
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Supply Systems ◽  
Deterministic Models ◽  
Working Pressure ◽  
Sensitive Parameter ◽  
The Impact ◽  
Supply Systems ◽  
Water Meter

Abstract Fluctuations in the network pressure of water supply systems affect hydraulic performance and water meter accuracy. The development of metering error curves requires steady-state conditions which are extremely rare in water distribution systems characterized by intermittent supply. Simple deterministic models are suggested and developed from monthly data collected over a 4-year period (2010–2014) for three most dominant meter models (Models 1–3) in the Kampala Water Distribution System (KWDS), Uganda. This study combines pressure and billing information at the same time to understand metering accuracy. Results showed that metering accuracy increased by 4.2, 8.4 and 2.9% when pressure was increased from 10 to 50 m for Models 1–3, respectively. Age did not influence the impact of pressure on meter accuracy. The most sensitive parameter in the model was the meter age. Metering accuracy was relatively constant after a period of 5 years. The least sensitive parameter was the working pressure which caused a slight change to the annual billed volume. The ability of the model to accurately predict the meter registration degenerated with an increasing annual billed volume. Model 2 meters were the best performing and probably the most suitable meters in the KWDS.

Rainwater Harvesting as a Distributed Resource

2010 ◽  
Author(s):  
John H. Whear
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Large Scale ◽  
Rainwater Harvesting ◽  
San Antonio ◽  
Water System ◽  
System Quality ◽  
Recycled Water

Explore the possibilities, difficulties, and benefits of large scale rainwater harvesting using recycled water distribution systems. This paper explores the growing use of recycled water and the possibilities that distribution systems have created. It investigates water quality of rainwater harvesting (RWH) systems and the quality of recycled water and their uses. It examines the amount of rain water available using aproximatly 10% of available roof area in the city and examines the benefits of large scale rainwater harvesting unique to San Antonio. An exhaustive search of published materials was conducted, coupled with communications with the Texas Water Development Board and the San Antonio Water System. Quality standards for recycled water were compared with known test results for harvested rainwater. With the use of mathematical models, a distributed rainwater harvesting systems was compared to a stand alone system. Connection to a distribution system reduces the cost of rainwater harvesting by eliminating the need for large amounts of storage, which can account for 50% of the total costs of a standalone system. With minor filtering and periodic quality checks, large structures may supply sufficient amounts of rainwater to justify being a source of water in a recycled water distribution system.

scholarly journals Non-invasive Biofouling Monitoring to Assess Drinking Water Distribution System Performance

2021 ◽  
Vol 12 ◽  
Author(s):  
Frances C. Pick ◽  
Katherine E. Fish ◽  
Stewart Husband ◽  
Joby B. Boxall
Keyword(s):  
Drinking Water ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Bulk Water ◽  
Water Supply Systems ◽  
Customer Contact ◽  
Drinking Water Distribution Systems ◽  
Drinking Water Distribution ◽  
Contact Data

Biofilms are endemic in drinking water distribution systems (DWDS), forming on all water and infrastructure interfaces. They can pose risks to water quality and hence consumers. Our understanding of these biofilms is limited, in a large part due to difficulties in sampling them without unacceptable disruption. A novel, non-destructive and non-disruptive biofilm monitoring device (BMD), which includes use of flow cytometry analysis, was developed to assess biofouling rates. Laboratory based experiments established optimal configurations and verified reliable cell enumeration. Deployment at three operational field sites validated assessment of different biofouling rates. These differences in fouling rates were not obvious from bulk water sampling and analysis, but did have a strong correlation with long-term performance data of the associated networks. The device offers the potential to assess DWDS performance in a few months, compared to the number of years required to infer findings from historical customer contact data. Such information is vital to improve the management of our vast, complex and uncertain drinking water supply systems; for example rapidly quantifying the benefits of improvements in water treatment works or changes to maintenance of the network.

scholarly journals E-Metering and Fault Detection in Smart Water Distribution Systems using Wireless Network

2019 ◽  
Vol 8 (11) ◽  
pp. 634-639
Keyword(s):  
Real Time ◽  
Sensor Network ◽  
Network Model ◽  
Rural Areas ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Large Scale ◽  
Water Distribution System ◽  
Smart Water

Water distribution system is a network that supplies water to all the consumers through different means. Proper means of providing water to houses without compromising in quantity and quality is always a challenge. As it is a huge network keeping track of the utilization is difficult for the utility. Hence through this project we come up with a solution to solve this issue. Current technologies like Low Power Wide Area Networks, LoRa and sensor deployment techniques have been in research and were also tested in few rural areas but issues due to hardware deployment and large scale real time implementation was a challenge hence through this system we aim to create and simulate a real time scenario to test a sensor network model that could be implemented in large scale further. This project aims in building a wireless sensor network model for a smart water distribution system. In this system there is bidirectional communication between the consumer and the utility. Each house has a meter through which the amount of water consumed is sent to the utility board. The data has two fields containing the house ID and the data (water consumed); it is being sent to the data collection unit (DCU) which in-turn sends it to the central server so that the consumption is monitored in real time. All this is simulated using NETSIM and MATLAB

scholarly journals Application of genetic programming to modeling pipe failures in water distribution systems

2010 ◽  
Vol 13 (3) ◽  
pp. 419-428 ◽  
Author(s):  
Qiang Xu ◽  
Qiuwen Chen ◽  
Weifeng Li
Keyword(s):  
Genetic Programming ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Pipe Failure ◽  
Beijing City ◽  
Failure Data ◽  
Processing Strategies ◽  
Gis Data ◽  
Failure Models

The water loss from a water distribution system is a serious problem for many cities, which incurs enormous economic and social loss. However, the economic and human resource costs to exactly locate the leakage are extraordinarily high. Thus, reliable and robust pipe failure models are demanded to assess a pipe's propensity to fail. Beijing City was selected as the case study area and the pipe failure data for 19 years (1987–2005) were analyzed. Three different kinds of methods were applied to build pipe failure models. First, a statistical model was built, which discovered that the ages of leakage pipes followed the Weibull distribution. Then, two other models were developed using genetic programming (GP) with different data pre-processing strategies. The three models were compared thereafter and the best model was applied to assess the criticality of all the pipe segments of the entire water supply network in Beijing City based on GIS data.

scholarly journals A Head Formulation for the Steady-State Analysis of Water Distribution Systems Using an Explicit and Exact Expression of the Colebrook–White Equation

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1163
Author(s):  
Mengning Qiu ◽  
Avi Ostfeld
Keyword(s):  
Steady State ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Solution Method ◽  
Water Distribution System ◽  
Academic Research ◽  
Exact Expression ◽  
Contamination Source

Steady-state demand-driven water distribution system (WDS) solution is the bedrock for much research conducted in the field related to WDSs. WDSs are modeled using the Darcy–Weisbach equation with the Swamee–Jain equation. However, the Swamee–Jain equation approximates the Colebrook–White equation, errors of which are within 1% for ϵ/D∈[10−6,10−2] and Re∈[5000,108]. A formulation is presented for the solution of WDSs using the Colebrook–White equation. The correctness and efficacy of the head formulation have been demonstrated by applying it to six WDSs with the number of pipes ranges from 454 to 157,044 and the number of nodes ranges from 443 to 150,630. The addition of a physically and fundamentally more accurate WDS solution method can improve the quality of the results achieved in both academic research and industrial application, such as contamination source identification, water hammer analysis, WDS network calibration, sensor placement, and least-cost design and operation of WDSs.

scholarly journals Cyber—Physical Attack Detection in Water Distribution Systems with Temporal Graph Convolutional Neural Networks

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1247
Author(s):  
Lydia Tsiami ◽  
Christos Makropoulos
Keyword(s):  
Neural Networks ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Attack Detection ◽  
Convolutional Network ◽  
Irreversible Damage ◽  
Physical Attack ◽  
Temporal Graph ◽  
Graph Neural Networks

Prompt detection of cyber–physical attacks (CPAs) on a water distribution system (WDS) is critical to avoid irreversible damage to the network infrastructure and disruption of water services. However, the complex interdependencies of the water network’s components make CPA detection challenging. To better capture the spatiotemporal dimensions of these interdependencies, we represented the WDS as a mathematical graph and approached the problem by utilizing graph neural networks. We presented an online, one-stage, prediction-based algorithm that implements the temporal graph convolutional network and makes use of the Mahalanobis distance. The algorithm exhibited strong detection performance and was capable of localizing the targeted network components for several benchmark attacks. We suggested that an important property of the proposed algorithm was its explainability, which allowed the extraction of useful information about how the model works and as such it is a step towards the creation of trustworthy AI algorithms for water applications. Additional insights into metrics commonly used to rank algorithm performance were also presented and discussed.

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