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The use of Artificial Neural Network (ANN) for modeling of Cu (II) ion removal from aqueous solution by flotation and sorptive flotation process
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Publication Date
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Ni(II), Pb(II), and Cu(II) from Industrial Wastewater by Using NF Membrane
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This article reviews the technical applicability of nanofiltration membrane process for the removal of nickel, lead, and copper ions from industrial wastewater.

Synthetic industrial wastewater samples containing Ni(II), Pb(II), and Cu(II) ions at various concentrations (50, 100, 150 and 200 ppm), under different pressures (1, 2, 3 and 4 bar), temperatures (10, 20, 30 and 40 oC), pH (2, 3, 4, 5 and 5.5), and flow rates (1, 2, 3 and 4 L/hr), were prepared and subjected treated by NF systems in the laboratory. Suitable NF membrane was chosen after testing a number of NF membranes (University of Technology-Baghdad), in terms of production and removal. NF system was capable of removing more than (85%, 78%, and 66% for Ni(II

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Publication Date
Fri Mar 08 2019
Journal Name
Desalination And Water Treatment
Xylenol orange removal from aqueous solution by natural bauxite (BXT) and BXT-HDTMA: kinetic, thermodynamic and isotherm modeling
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Sorption is a key factor in removal of organic and inorganic contaminants from their aqueous solutions. In this study, we investigated the removal of Xylenol Orange tetrasodium salt (XOTS) from its aqueous solution by Bauxite (BXT) and cationic surfactant hexadecyltrimethyl ammonium bromide modified Bauxite (BXT-HDTMA) in batch experiments. The BXT and BXT-HDTMA were characterized using FTIR, and SEM techniques. Adsorption studies were performed at various parameters i.e. temperature, contact time, adsorbent weight, and pH. The modified BXT showed better maximum removal efficiency (98.6% at pH = 9.03) compared to natural Bauxite (75% at pH 2.27), suggesting that BXT-HDTMA is an excellent adsorbent for the removal of XOTS from water. The equ

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Publication Date
Tue Jan 01 2019
Journal Name
Desalination And Water Treatment
Xylenol orange removal from aqueous solution by natural bauxite (BXT) and BXT-HDTMA: kinetic, thermodynamic and isotherm modeling
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Crossref (6)
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Publication Date
Tue Jan 01 2019
Journal Name
Desalination And Water Treatment
Xylenol orange removal from aqueous solution by natural bauxite (BXT) and BXT-HDTMA: kinetic, thermodynamic and isotherm modeling
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Crossref (6)
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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

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Publication Date
Fri Jan 26 2024
Journal Name
Iraqi Journal Of Science
Removal of Cu (ll) From Aqueous Solution Using Polyacrylic Acid Hydrogel Beads as Adsorbent
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In this article, the adsorption of Cu(ll) ion from aqueous solution into polyacrylic acid
(PAA) hydrogel bead has been investigated using a batch method of different
temperature (10-30 °C) and different contact time (1-48 hr) to reach the equilibrium of
adsorption. Initial concentration and adsorption capacity of the adsorbents is presented,
the time required to reach a maximum capacity of bead was about 24hr. The temperature
effect on adsorption was studied and the experimental data have been analyzed using the
Langmuir and freundlich isotherm models. The adEsorption capacity at equilibrium was
found to be 142.68 mg/g; more than 95% of studied cation was removed by the
adsorbent. The process is very efficient es

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Publication Date
Tue Feb 28 2017
Journal Name
Journal Of Engineering
Removal of Lead (II) from Aqueous Solution Using Chitosan Impregnated Granular Activated Carbon
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The use of biopolymer material Chitosan impregnated granular activated carbon CHGAC as adsorbent in the removal of lead ions  pb.2+   from aqueous solution was studied using batch adsorption mode. The prepared CHGAC was characterized by Scanning Electronic Microscopy (SEM) and atomic-absorption  pectrophotometer. The adsorption of lead ions onto Chitosan-impregnated granular activated carbon was examined as a function of adsorbent weight, pH and
contact time in Batch system. Langmuir and Freundlich models were employed to analyze the resulting experimental data demonstrated that better fitted by Langmuir isotherm model than Freundlich model, with good correlation coefficient. The maximum adsorption capacity calculated f

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Publication Date
Mon Oct 01 2018
Journal Name
Conference: First International Conference On Water Resources
Modeling BOD of the Effluent from Abu-Ghraib Diary Factory using Artificial Neural Network October 2018
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The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Fault Location of Doukan-Erbil 132kv Double Transmission Lines Using Artificial Neural Network ANN
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Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

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Publication Date
Fri Jan 26 2024
Journal Name
Iraqi Journal Of Science
Removal of Iron (Iii) Ion from Aqueous Solution using Polyacrylic Acid Hydorgel Beads as Adsorbent
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This research focuses on the removal and adsorption of Fe (III) ion using a low cost commercial polyacrylic acid hydrogel beads as adsorbent. The effects of time, initial concentration and pH on the metal ion adsorption capacity were investigated. The regeneration of the hydrogel bead and recovery of the metal ion adsorbed were study. The adsorption isotherm models were applied on experimental data and it is shown that the Langmuir model was the best one for Fe (III) ion removal. The maximum capacity was calculated. First-order and second- order kinetic models were used and it is shown that the experimental data was in reliable compliance with the first- order model with R2 value of (0.9935, 0.9011, 0.9695, 0.9912) for all concentrations

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