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Influence of A River Water Quality on The Efficiency of Water Treatment Using Artificial Neural Network
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Tigris River is the lifeline that supplies a great part of Iraq with water from north to south. Throughout its entire length, the river is battered by various types of pollutants such as wastewater effluents from municipal, industrial, agricultural activities, and others. Hence, the water quality assessment of the Tigris River is crucial in ensuring that appropriate and adequate measures are taken to save the river from as much pollution as possible. In this study, six water treatment plants (WTPs) situated on the two-banks of the Tigris within Baghdad City were Al Karkh; Sharq Dijla; Al Wathba; Al Karama; Al Doura, and Al Wahda from northern Baghdad to its south, that selected to determine the removal efficiency of turbidity and the water quality index used to assess the quality of water for drinking purposes, in addition to finding the model based on past information to predict the quality of treated wastewater produced in each WTP using an artificial neural network (ANN) approach. The selected parameters for this study were turbidity, total hardness, total solids, suspended solids, and alkalinity. The results showed that all the WTPs possessed a high rate of efficiency in the removal of turbidity from raw water. Also, the results of the water quality index for all WTPs were classified over a study period of three years from 2015 to 2017 as being a good water quality and based on these results, the water treatment plants can be considered to be doing efficient water treatment process. The ANN model has been found at all WTPs to have a coefficient of determination (R2) for expected models was more than 0.7 to provide a WQI prediction tool that can be used with a moderate level of predictive acceptance to describe the suitability of WTP water quality for drinking purposes.

Publication Date
Mon Sep 07 2020
Journal Name
Environmental Science And Pollution Research
The biosorption of reactive red dye onto orange peel waste: a study on the isotherm and kinetic processes and sensitivity analysis using the artificial neural network approach
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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Use Dynamic Bayesian network to estimate the reliability of Adamia Water Network
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Abstract\

In this research, estimated the reliability of water system network in Baghdad was done. to assess its performance during a specific period. a fault tree through static and dynamic gates was belt and these gates represent logical relationships between the main events in the network and analyzed using dynamic Bayesian networks . As it has been applied Dynamic Bayesian networks estimate reliability by translating dynamic fault tree to Dynamic Bayesian networks and reliability of the system appreciated. As was the potential for the expense of each phase of the network for each gate . Because there are two parts to the Dynamic Bayesian networks and two part of gate (AND), which includes the three basic units of the

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Publication Date
Tue Aug 07 2018
Journal Name
Indian Journal Of Natural Sciences
Evaluation of Drinking Water Quality in Al Wathba Treatment Plant in Baghdad City-Iraq
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Publication Date
Mon Apr 07 2025
Journal Name
Al-nahrain Journal For Engineering Sciences
Design of Reverse Osmosis Water Treatment Unit Using Lanxess Lewaplus2
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Basrah is the richest town and the economic capital of Iraq. It suffers from lack of drinking water. This project is a dream to supply drinking water to Basrah citizens within WHO standards. Water should pass sedimentation and filtration stages before interring reverse osmosis unit. The design is carried out using lewaplus2 software. Several parameters should be selected in the design step membrane type, number of stages, number per element in each stage, and the recovery percentage. An optimization is carried out using Minitab ver. 18 for the acceptable limit of TDS and minimum cost and it was found that the optimum conditions were 52% for first stage, the numbers of vessels are 20 for both the first and second stage. In addition,

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Publication Date
Mon Jan 01 2018
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Treatment of Sulfate in Sand by Using Magnetic Water Process
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One of the most important problems in concrete production in Iraq and other country is the high sulfate content in sand that led to damage of concrete and hence reduces its compressive strength and may leads to cracking due to internal sulfate attack and delay ettringite formation. The magnetic water treatment process is adopted in this study. Many samples with different SO3 content are treated with magnetic water (12, 8, 4 and 2)L that needed for each 1kg of sand with the magnetic intensity (9000 and 5000) Gaus. The magnetic water needed is reduced with less SO3 content in sand. The ACI 211.1-91 concrete mix design was used in this research with slump range (75- 100) mm and the specified compressive strength (35MPa). The compressive streng

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Publication Date
Wed Oct 23 2013
Journal Name
Journal Of Microbiology And Biotechnology Research
Optimization of flocculation conditions of exopolysaccharide biofloculant from Azotobacter chrococcum and its potential for river water treatment
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Bacteria strain H8, which produces high amount of exopolysaccharide (EPS), was isolated from soil, and identified as strain of Azotobacter chrococcum by its biochemical /physiological characteristics, EPS was extracted, partially purified and used as bioflocculant. The biochemical analysis of the partially purified EPS revealed that it was an alginate. analysis of EPS by Fourier transform infrared spectrometry (FTIR) show that the -OH groups present in bioflocculant are clearly seen at 3433.06 cm-1, the peaks attributed to the -CH3 groups present at 2916.17 cm-1 , and some distinct peaks such as carboxyl group showed strong absorption bands at 1604.66 cm-1, 1411.80 cm-1 and 1303.79 cm-1 indicate the chemical structure of alginate. The effe

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Publication Date
Thu Oct 31 2024
Journal Name
Iraqi Geological Journal
Artificial Neural Network Application to Permeability Prediction from Nuclear Magnetic Resonance Log
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Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
The effect of wastewater disposal on the water quality and phytoplankton in Erbil wastewater channel.
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In this study, phytoplankton density, chlorophyll-a, and selected physico- chemical parameters were investigated in Erbil wastewater channel. The surveys were carried out monthly from May 2003 to April 2004. Samplings were established on three sites from headwaters to the mouth. The results showed that pH was in alkaline side of neutrality, with significant differences (P<0.05) between sites 1 and 3. TSS concentration decreased from site 1 toward site 2 (mean value, 80.15 to 25.79 mg.l-1). A clear gradual increase in mineral content (TDS) observed from site one of the channel towards the mouthpart. Soluble reactive phosphate has a concentration maximum mean value reached 48.4 µg.l-1 which is recorded in site 2. A high positive relat

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Publication Date
Tue Nov 01 2022
Journal Name
Journal Of Engineering
Artificial Neural Network Model for Wastewater Projects Maintenance Management Plan
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Wastewater projects are one of the most important infrastructure projects, which require developing strategic plans to manage these projects. Most of the wastewater projects in Iraq don’t have a maintenance plan. This research aims to prepare the maintenance management plan (MMP) for wastewater projects. The objective of the research is to predict the cost and time of maintenance projects by building a model using ANN. The research sample included (15) completed projects in Wasit Governorate, where the researcher was able to obtain the data of these projects through the historical information of the Wasit Sewage Directorate. In this research artificial neural networks (ANN) technique was used to build two models (cost

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Publication Date
Sat May 01 2021
Journal Name
Https://www.researchgate.net/journal/journal-of-physics-conference-series-1742-6596
The management of water distribution network using GIS application case study: AL-Karada area
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Abstract<p>Clean water supply is one of the major factors contributing significantly to society’s socio-economic transformation by improving living standards, health, and increasing productivity. It is imperative to plan and construct appropriate water supply systems in modern society, which supply various segments of society with safe drinking water according to their requirements to ensure adequate and quality water supply. In the current study, here was an attempt to develop a model for geographic information systems to manage the assets of the water distribution networks in the Karrada region and to evaluate the network geometrically, and from the results of the engineering analysis of the</p> ... Show More
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