نوع مقاله : مقاله پژوهشی
نویسندگان
چکیده
مادة شیمیایی کلر برای چندین دهه، به‌عنوان بهترین مادة ضدعفونی‌کننده یا بخشی از فرایند تصفیة آب آشامیدنی مورد استفاده قرار گرفته است؛ با وجود این، غلظت‌های کلر بیش از 3 میلی‌گرم در لیتر در آب آشامیدنی، برای سلامتی انسان خطرناک است. در این پژوهش، شبکة توزیع آب منطقة وحیدیه، واقع در غرب استان تهران، به‌وسیلة مدل عددی WaterGEMS شبیه‌سازی شد. در این شبیه‌سازی، اصول حاکم بر طراحی شبکههای آبرسانی، برای نائل شدن به تعدادی از پارامترهای کیفی مربوط به مادة شیمیایی کلر (از جمله سن آب، غلظت کلر و ردیابی آن)، رعایت و در این مدل‌سازی، سه سناریوی مختلف با افزوده شدن کلر غیرمجاز (بیش از 3 میلی‌گرم در لیتر) به مخزن‌های توزیع آب و مخازن تنظیم فشار، در نظر گرفته شد. همچنین در مدل‌سازی، به بررسی تعدادی از پارامترهای کمّی (مانند دبی و سرعت جریان آب و افت انرژی) نیز در لوله‌های شبکه آبرسانی منطقه وحیدیه، پرداخته شده و نتایج مدل‌سازی برای سه لولة منتخب در نقاط مختلف شبکه مورد بحث قرار گرفت. نتایج حاصل نشان داد، محاسبة سن آب در لولة شماره 18 حدود 3 برابر سن آب در لولة شماره 168 است. غلظت کلر در لوله شماره 168 (لوله نزدیک‌تر به مخازن آب)، 10% بیشتر از دو لوله دیگر و بسیار نزدیک به غلظت کلر در مخازن آب بود. با توجه به موضوع ردیابی کلر برای پی بردن به منبع آلودگی، آب لولة شماره293، یقیناً از مخزن تنظیم فشار شمارة 2 تأمین شده است. طبق نتایج مدل‌سازی پارامترهای کمّی، حداکثر سرعت جریان در لولة شماره 18 (0.3 متر در ثانیه) به دست آمد که نشان از احتمال رسوب‌گذاری املاح موجود در آب دارد.
کلیدواژه‌ها
عنوان مقاله [English]
Numerical simulation of quantitative and qualitative parameters in water supply networks by WaterGEMS
نویسندگان [English]
- Mahdi Ebrahimi
- Mirali Mohammadi
چکیده [English]
WaterGEMS is a software that provides a numerical model, which simulates different parameters in water distribution systems based on the hydraulics principles. The most remarkable chemical substance used in water refinement procedure is chlorine. Therefore, WaterGEMS software models the chlorine to detect its concentration in each pipe of the water distribution system. If the chlorine concentration exceeds 3 mg/lit, it would be dangerous for the Man health. In addition, the model may calculate water age in water distribution networks and trace the chlorine substance. In this research, the chlorine concentration, water age and chlorine trace parameters have been simulated using WaterGEMS for a case study: Vahidieh district (located on the west part of Tehran province). Meanwhile, other quantitative parameters including flow discharge, flow velocity and water head loss in pipe networks, have also been calculated in Vahidieh water distribution network system. This is done because there are important relationships between qualitative and quantitative parameters for the optimization design of water distribution networks. For more comfortable comparison and interpretation of the above concept, three pipes in different places of Vahidieh water distribution network have been chosen (i.e. 18th,168th and 293th pipes put in the left, middle and right side of water distribution network, respectively).
The innovation of the present study was to provide quantitative and qualitative parameters for the simulation of Vahidieh region, where it has not yet been found out up to now. In addition, modeling all the mentioned parameters will result in a comprehensive view to the design of water distribution networks. Aghasi (2018) presented a model using WaterGEMS to determine appropriate points for chlorine injection in Mashhad water distribution network and located the appropriate points based on the network geometry, pipes’ diameter and consumption pattern . Javadinejad et al. (2019) utilized a pump and gravitational statuses in Semirom water distribution using WaterGEMS. They stated that in pumping method, water qualitative management may guarantee a better system. Vidhi and Geeta (2019) simulated a rural region in India using WaterGEMS indicating the remained pipes’ chlorine concentration are at standard levels (i.e. less than 3 mg/lit).
In the software, the analysis of water distribution networks is given step by step as: Step 1, network drawing based on the nodes’ coordinates, pipes’ situation, reservoirs, tanks and other elements. Step 2, defining the network hydraulic traits. Step 3, defining the distribution network for hydraulic performance. Step 4, defining the network analysis method. After that by running the software, the network parameters would be obtained. Finally, the network quantitative and qualitative results may be achieved. The population of Vahidieh town’ water distribution network, where used as a case study, will be 78600 persons at the end of 30 years design period resulting in total water consumption of 215 lit/day per capita. While the amount of water consumption in the region has been estimated 195 lit/s. There are two tanks and two reservoirs in the new water distribution network system. The volume of each tank and reservoir is 500 and 5000 m3, respectively. Meanwhile, a chlorination house with the maximum chlorine injection of 3 mg/lit has been designed for disinfection. The pipes were made of polyethylene. For modeling Vahidieh town water distribution network using WaterGEMS software, at first, the nodes and pipes were drawn using AutoCAD software. Then, the reformed information were imported to the WaterGEMS software. In this step, it is necessary to extract nodes’ altitude codes from ArcView software. Then, other elements of network, consumption pattern and different scenarios were defined and finally, the reports were analyzed and the results were obtained.
The numerical simulation reproduced the complex flow patterns in the pipes network associated with a particular water consumption in the Vahidieh water distribution network that are presented as a case study. Based on the analysis made by applying WaterGEMS, the following results were obtained:
The chlorine concentration in 18th, 168th and 293th pipes were selected and have been studied, in more details. Meanwhile, three defined scenarios were used: (1). The primary concentration in nodes, tanks, pumps, valves and reservoirs were 0.1, 0.5, 1, 1 and 2 mg/lit, respectively. (2). The chlorine concentration reaches to 10 mg/lit in reservoirs, while its concentration is the 1st scenario in other ingredients. (3). The chlorine concentration reaches to 5 mg/lit in tanks, while its concentration is the 2nd scenario in other ingredients.
Based on the obtained numerical model reports, the water age in the 18th pipe was higher than the 168th and 293th. According to the Vahidieh town population distribution, the 18th pipe was surrounded by less population in comparison with the other two pipes. In addition, in, the maximum water age of the 18th pipe was 3 times of the 168th pipe. According to the WaterGEMS reports, under different scenarios, the chlorine concentration in 168th pipe was equal to the injected chlorine concentration to the reservoirs (the pipe which is closer to reservoirs). In addition, the 168th pipe chlorine concentration was 10% higher than the other two pipes in all the scenarios. The chlorine concentration computation in the selected pipes indicates much higher influence on the reservoirs’ chlorine concentration than chlorine concentration in water distribution network pipes. Furthermore, based on the third scenario, when the chlorine concentration increases in the tanks, there is not tangible variation in pipes chlorine concentration because of the higher volume of reservoirs in comparison with the tanks' volume. The obtained results reveals that the maximum water provision probability of 18th pipe from the 1st tank is about 45%. Additionally, the 168th pipe’s water provision probability from two reservoirs is the same. Also, the 293th pipe water has surely been supplied from the 2nd tank. In addition, the flow velocity, water head loss and water discharge can be studied in each 24-hour period based on hourly consumption pattern. Based on the WaterGEMS outputs, the maximum water flow velocity in the 18th pipe is 0.3 m/s. This result is reasonable due to the higher water age in the pipe in comparison with the other two pipes. As a consequent, it seems that sedimentation probably occurs along the 18th pipe. Moreover, the 168th pipe reaches a maximum head loss of 0.4 m, and the 293th pipe receives a maximum water discharge of 8 lit/s.
کلیدواژه‌ها [English]
- chlorine concentration
- chlorine trace
- quantitative and qualitative parameters
- Vahidiyeh region
- water age
- WaterGEMS numerical model
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