A robust simulator of pressure-dependent consumption in Python
Modeling of pressure-dependent users’ consumption is mandatory to simulate accurately the hydraulics of water distribution networks (WDNs). Several software solutions already exist for this purpose, but none of them actually permits the easy integration and testing of new physical processes. In this...
Main Authors: | , , |
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Format: | Article |
Language: | English |
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IWA Publishing
2024-01-01
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Series: | Journal of Hydroinformatics |
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Online Access: | http://jhydro.iwaponline.com/content/26/1/284 |
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author | Camille Chambon Olivier Piller Iraj Mortazavi |
author_facet | Camille Chambon Olivier Piller Iraj Mortazavi |
author_sort | Camille Chambon |
collection | DOAJ |
description | Modeling of pressure-dependent users’ consumption is mandatory to simulate accurately the hydraulics of water distribution networks (WDNs). Several software solutions already exist for this purpose, but none of them actually permits the easy integration and testing of new physical processes. In this paper, we propose a new Python simulator that implements a state-of-the-art pressure-dependent model (PDM) of users’ consumptions based on the Wagner’s pressure–outflow relationship (POR). We tested our simulator on eight large and complex WDNs, for different levels of users’ demands. The results show similar precision and efficiency to the ones obtained by the authors of the original model with their MATLAB implementation. Moreover, in case of fully satisfied users’ demands, our simulator provides the same results as EPANET 2.0 in comparable computational times. Finally, our simulator is integrated into the open-source, collaborative, multi-platform, and Git versioned Python framework OOPNET (Object-Oriented Python framework for water distribution NETworks analyses); thus, it can be easily reused and/or extended by a large community of WDN modelers. All this work represents a preliminary step before the incorporation of new processes such as valves, pumps, and pressure-dependent background leakage outflows.
HIGHLIGHTS
A new simulator of pressure-dependent consumption in water distribution network.;
Coded in Python, based on a state-of-the-art MATLAB model, easy to extend.;
Numerical experiments on networks composed of up to 19,647 pipes and 17,986 nodes.;
Instabilities handled through regularization and line search along the Newton descent.;
Preliminary step for integration of new processes and first contribution to OOPNET.; |
first_indexed | 2024-03-08T03:17:43Z |
format | Article |
id | doaj.art-6e331e923ad04396af5601d0c579a399 |
institution | Directory Open Access Journal |
issn | 1464-7141 1465-1734 |
language | English |
last_indexed | 2024-04-24T08:46:31Z |
publishDate | 2024-01-01 |
publisher | IWA Publishing |
record_format | Article |
series | Journal of Hydroinformatics |
spelling | doaj.art-6e331e923ad04396af5601d0c579a3992024-04-16T13:34:57ZengIWA PublishingJournal of Hydroinformatics1464-71411465-17342024-01-0126128430310.2166/hydro.2023.218218A robust simulator of pressure-dependent consumption in PythonCamille Chambon0Olivier Piller1Iraj Mortazavi2 INRAE, UR ETTIS, Cestas F-33612, France INRAE, UR ETTIS, Cestas F-33612, France CNAM, M2N, Paris F-75003, France Modeling of pressure-dependent users’ consumption is mandatory to simulate accurately the hydraulics of water distribution networks (WDNs). Several software solutions already exist for this purpose, but none of them actually permits the easy integration and testing of new physical processes. In this paper, we propose a new Python simulator that implements a state-of-the-art pressure-dependent model (PDM) of users’ consumptions based on the Wagner’s pressure–outflow relationship (POR). We tested our simulator on eight large and complex WDNs, for different levels of users’ demands. The results show similar precision and efficiency to the ones obtained by the authors of the original model with their MATLAB implementation. Moreover, in case of fully satisfied users’ demands, our simulator provides the same results as EPANET 2.0 in comparable computational times. Finally, our simulator is integrated into the open-source, collaborative, multi-platform, and Git versioned Python framework OOPNET (Object-Oriented Python framework for water distribution NETworks analyses); thus, it can be easily reused and/or extended by a large community of WDN modelers. All this work represents a preliminary step before the incorporation of new processes such as valves, pumps, and pressure-dependent background leakage outflows. HIGHLIGHTS A new simulator of pressure-dependent consumption in water distribution network.; Coded in Python, based on a state-of-the-art MATLAB model, easy to extend.; Numerical experiments on networks composed of up to 19,647 pipes and 17,986 nodes.; Instabilities handled through regularization and line search along the Newton descent.; Preliminary step for integration of new processes and first contribution to OOPNET.;http://jhydro.iwaponline.com/content/26/1/284numerical optimizationpressure-dependent model (pdm)python programing languageuser’s consumptionwater distribution network (wdn) |
spellingShingle | Camille Chambon Olivier Piller Iraj Mortazavi A robust simulator of pressure-dependent consumption in Python Journal of Hydroinformatics numerical optimization pressure-dependent model (pdm) python programing language user’s consumption water distribution network (wdn) |
title | A robust simulator of pressure-dependent consumption in Python |
title_full | A robust simulator of pressure-dependent consumption in Python |
title_fullStr | A robust simulator of pressure-dependent consumption in Python |
title_full_unstemmed | A robust simulator of pressure-dependent consumption in Python |
title_short | A robust simulator of pressure-dependent consumption in Python |
title_sort | robust simulator of pressure dependent consumption in python |
topic | numerical optimization pressure-dependent model (pdm) python programing language user’s consumption water distribution network (wdn) |
url | http://jhydro.iwaponline.com/content/26/1/284 |
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