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Corrosion of Carbon Steel in Oxygen and NaCl Concentration Cells: the Influence of Solution Temperature and Aeration
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Corrosion rate tests were carried out on carbon steel under concentration cells conditions of oxygen and sodium chloride. The effect of aeration in one compartment on the corrosion rate of both coupled metals was determined. In addition, the effects of time and temperatures on the corrosion rate of both coupled metals and galvanic currents between them were investigated. Corrosion potentials for the whole range of operating conditions under concentration cell conditions were also studied.   The results showed that under aeration condition, the formation of concentration cell caused a considerable corrosion rate of the Carbon steel specimens coupled in different concentrations of O2 and NaCl due to the galvanic effect. Aerating one compartment caused a noticeable increase in the corrosion rate of the coupled specimen in the other compartment due to the galvanic effect. Increasing temperature caused unstable trends in the free and galvanic corrosion potentials. Increasing the temperature led to an increase in the corrosion rate for both metals.

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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Polluted Water Sensor Based on Carbon Quantum Dots/Alq3 Using Drop Casting and Spin Coating Techniques
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Water quality sensors have recently received a lot of attention due to their impact on human health. Due to their distinct features, environmental sensors are based on carbon quantum dots (CQDs). In this study, CQDs were prepared using the electro-chemical method, where the structural and optical properties were studied. These quantum dots were used in the environmental sensor application after mixing them with three different materials: CQDs, Alq3 polymer and CQDs and Alq3 solutions using two different methods: drop casting and spin coating, and depositing them on silicon. The sensitivity of the water pollutants was studied for each case of the prepared samples after measuring the change in resistance of the samples at a temperature of

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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Surface Roughness after Turning of Duplex Stainless Steel (DSS)
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Feed Forward Back Propagation artificial neural network (ANN) model utilizing the MATLAB Neural Network Toolbox is designed for the prediction of surface roughness of Duplex Stainless Steel during orthogonal turning with uncoated carbide insert tool. Turning experiments were performed at various process conditions (feed rate, cutting speed, and cutting depth). Utilizing the Taguchi experimental design method, an optimum ANN architecture with the Levenberg-Marquardt training algorithm was obtained. Parametric research was performed with the optimized ANN architecture to report the impact of every turning parameter on the roughness of the surface. The results suggested that machining at a cutting speed of 355 rpm with a feed rate of 0.07 m

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Publication Date
Fri Aug 11 2017
Journal Name
Journal Of Engineering
Thermo Elastic Analysis of Carbon Nanotube-Reinforced Composite Cylinder Utilizing Finite Element Method with the Theory of Elasticity
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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Intelligent Systems And Applications In Engineering
Artificial Intelligence Based Statistical Process Control for Monitoring and Quality Control of Water Resources: A Complete Digital Solution
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Publication Date
Fri Jun 29 2018
Journal Name
Journal Of Engineering
Experimental Investigation of Short Square Normal and Hybrid Fiber Reactive Powder Concrete Columns Subjected to Chloride Solution Attack
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In this research, the structural behavior of reinforced concrete columns made of normal and hybrid reactive powder concrete (hybrid by steel and polypropylene fibers) subjected to chloride salts with concentration was 8341.6 mg/l. The study consists of two parts, the first one is experimental study and the second one is theoretical analysis.  Three main variables were adopted in the experimental program; concrete type, curing type and loading arrangement. Twenty (120x120x1200) mm columns were cast and tested depending on these variables. The samples were reinforced using two different bars; Ø8 for ties and Ø12 with minimum longitudinal reinforcement (0.01Ag). The specimens were divided into two main groups based o

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
The influence of organizational culture on the organizational performance of educational institutions (University of Technology as a model)
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The organizational culture is an effective control mechanism that dictates the behavior of employees and according to their intellectual and social orientations, so it is considered a more powerful way to control employee orientations and determine their management according to organizational rules and regulations, as it was one of the most important factors determining the performance of organizations, while organizational performance is a measure of what the organization has achieved from the objectives of the scheme To ensure that it faces various changes and remains within the global competition, and to reach that it was necessary to identify the most prominent and most important research problems in knowing the extent of com

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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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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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Scopus (16)
Crossref (15)
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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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Scopus (16)
Crossref (15)
Scopus Clarivate Crossref