Intelligent chlorination in water distribution networks: Integrating genetic algorithm and EPANET fusion

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F25%3A00013508" target="_blank" >RIV/46747885:24220/25:00013508 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/46747885:24620/25:00013508

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S2307410825000690" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2307410825000690</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.kjs.2025.100425" target="_blank" >10.1016/j.kjs.2025.100425</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Intelligent chlorination in water distribution networks: Integrating genetic algorithm and EPANET fusion

Popis výsledku v původním jazyce

The primary goal of chlorination, a chemical treatment process employed in water distribution networks (WDNs), is to safeguard public health by disinfecting potable water. This research delves into the hydraulic and qualitative analysis of WDNs in the Golestan district of Ahwaz city, Iran, utilizing a demand-based methodology integrating genetic algorithm (GA) and Environmental Protection Agency Network Evaluation Tool (EPANET) simulation software. The investigation incorporates varied concentrations of booster chlorination, and a re-qualitative analysis is subsequently performed. Three distinct scenarios, each employing one, two, and three booster pumps, are conceptualized. A quality performance indicator is developed to enhance comprehension and facilitate a comprehensive water assessment. To optimize the quality performance index (QPI), the GA is employed with an objective function, i.e., determining the most effective placement of chlorine injection pumps. The results reveal that the network performance index achieved percentages of 78%, 78%, and 80% across the three scenarios. Moreover, the water quality in the second and third scenarios attains notably high acceptability levels, highlighting the efficacy of the proposed chlorination strategy.

Název v anglickém jazyce

Intelligent chlorination in water distribution networks: Integrating genetic algorithm and EPANET fusion

Popis výsledku anglicky

The primary goal of chlorination, a chemical treatment process employed in water distribution networks (WDNs), is to safeguard public health by disinfecting potable water. This research delves into the hydraulic and qualitative analysis of WDNs in the Golestan district of Ahwaz city, Iran, utilizing a demand-based methodology integrating genetic algorithm (GA) and Environmental Protection Agency Network Evaluation Tool (EPANET) simulation software. The investigation incorporates varied concentrations of booster chlorination, and a re-qualitative analysis is subsequently performed. Three distinct scenarios, each employing one, two, and three booster pumps, are conceptualized. A quality performance indicator is developed to enhance comprehension and facilitate a comprehensive water assessment. To optimize the quality performance index (QPI), the GA is employed with an objective function, i.e., determining the most effective placement of chlorine injection pumps. The results reveal that the network performance index achieved percentages of 78%, 78%, and 80% across the three scenarios. Moreover, the water quality in the second and third scenarios attains notably high acceptability levels, highlighting the efficacy of the proposed chlorination strategy.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10700 - Other natural sciences

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Kuwait Journal of Science>

ISSN

2307-4108

e-ISSN

—

Svazek periodika

52

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

KW - Kuvajtský stát

Počet stran výsledku

13

Strana od-do

—

Kód UT WoS článku

001487697300001

EID výsledku v databázi Scopus

2-s2.0-105003972984