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Enregistrement W6963934780 · doi:10.22126/atwe.2024.9839.1066

Intermittent water optimized supply considering consumption pattern change in water distribution network

2023· article· en· W6963934780 sur OpenAlexaff

Notice bibliographique

RevueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Langueen
DomaineEngineering
ThématiqueWater Systems and Optimization
Établissements canadiensNational Research Council Canada
Organismes subventionnairesnon disponible
Mots-clésWater supplyPopulationConsumption (sociology)Non-revenue waterPressure dropDrop (telecommunication)Energy consumption

Résumé

récupéré en direct d'OpenAlex

IntroductionClimate change and population increase have caused an increase in consumption in the existing water distribution networks, as a result, an increase in the discharge in the pipes and a decrease in the pressure in the nodes. The decrease in pressure makes some consumers unable to receive the required water. To solve this problem, long-term and short-term solutions have been proposed. Replacing pipes with pipes with a larger diameter is one of the solutions. But it requires considerable time and money. Intermittent supply of water can be used in existing networks to solve the problem.TazeAbad network has a large pressure drop during peak hours. The reason for this is the low diameter of the main pipes, which cause a large drop in the pressure as the consumption increases and the discharge increases. In this study, in order to improve justice and increase water supply in this network, optimal intermittent supply of water was done for 6 areas of this network.MethodologyThe Intermittent supply of water is usually done based on pressure-based hydraulic analysis. In case, the consumers will also store the needs of other hours. In other words, the consumption pattern in continuous supply cannot be used for Intermittent supply. In this research, the Emitter method is used for the hydraulic analysis of the network. In this hydraulic analysis, the amount of water delivered to the node is a function of pressure.Intermittent supply for 6 areas of the water distribution network of TazeAbad city was optimized in 12, 8 and 6 hours with the aim of supplying the required water and high two-objective by using single-objective and two-objective Harmony Search algorithm. In the hydraulic model, the pressure-based hydraulic analysis method and the Emitter method were used to determine the discharge of the nodes and the results were compared. In different scenarios, the possibility of supplying water in 4, 3 and 2 time intervals was investigated.Results and discussionIn all scenarios, the results of pressure-based hydraulic analysis method are located in all areas of Tazehabad city during peak hours. In this method, despite the high distribution uniformity coefficient, the amount of water delivered to consumers is less than their needs in the hour of supply. At present, in TazeAbad distribution network, consumers receive more water at the existing pressures than the pressure-based method.In the Emitter method, in all scenarios, the distribution uniformity is lower than the pressure-based method. But in this method, the supply percentage is much higher. So that more than 95% of customers' demands have been met in 12-hour supply.By reducing the water supply time, the percentage of supply has decreased in both methods. In the single-objective algorithm, the ratio of supplied water to the required water is more than the double-objective algorithm. But the uniformity of the distribution has increased in the double-objective algorithm. In all scenarios, water delivery in the pressure-based method was in one time interval for all areas, but in the Emitter method, water was usually delivered in 2 time intervals.In TazeAbad network, if water is supplied in 2 shifts, the maximum discharge in the network is more than the maximum discharge of the existing conditions of the network. But if water is supplied in 3 and 4 time intervals, the maximum discharge will be closer to the maximum discharge of the network. The difference between the maximum and minimum network discharges in the two-objective algorithm was lower than the single-objective algorithm. The supply of water in 4 time intervals has had the least changes in discharge and consumption coefficients.Conclusions According to the scenarios reviewed in TazeAbad network, water supply in 8 hours was chosen as the best option. In this case, the ratio of supplied water to required water will be around 70% and the uniformity of distribution will be around 87%. The maximum discharge in the water distribution network is almost equal to the maximum discharge in the current conditions. Also, the range of discharge changes and consumption coefficients is lower than the current conditions. In other words, pressure changes in the network will be less than the current conditions.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,269
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,002
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,210
Tête enseignante GPT0,457
Écart entre enseignants0,247 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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