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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
Sun Dec 06 2015
Journal Name
Baghdad Science Journal
Generated and shifted of Ion beams By Electrostatic Lenses (Einzel lens)
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In this paper, the path of the extracted and focused ions by the electrostatic lense having three electrodes of the same size and shape have been studied. However, the first and third electrodes had a different potential from the second electrode and the distance between any three electrodes was (d).The beams of the charged particles were controlled by using electrostatic fields which are used for accelerating and focusing. This paper focuses also on the effect of electrodes potentials on ion beam focusing. It is found that the best focusing was achieved when the values of the potential of the first and third electrode are equal to half of the value of the second electrode. Concerning transmiting and acumulating the ions beams, the study sh

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Publication Date
Wed Jun 18 2014
Journal Name
Desalination And Water Treatment
Removal of zinc from contaminated groundwater by zero-valent iron permeable reactive barrier
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Publication Date
Wed Oct 17 2018
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
ESTIMATION OF MUNICIPAL SOLID WASTE GENERATION AND LANDFILL VOLUME GENERATION AND LANDFILL VOLUME USING ARTIFICIAL NEURAL NETWORKS
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Publication Date
Mon Jan 01 2018
Journal Name
Eco Env And Cons
Histological changes resulting from the use of sublethal concentrations from insecticide.....
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Publication Date
Sun Dec 01 2024
Journal Name
Nordic Concrete Research
Evaluating Concrete Strength Under Various Curing Conditions Using Artificial Neural Networks
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Abstract<p>This study examines the impact of different curing methods on the compressive strength of concrete. It investigates techniques such as air curing, periodic water spraying, full water submersion, and polyethylene encasement. Artificial neural network models were employed to evaluate the compressive strength under each curing condition. A model for calculating compressive strength that considers surrounding conditions was created using an artificial neural network. The current study’s figures were generated using this model. The research thoroughly examined the impact of curing environments and concrete mix components on strength properties, taking into account factors such as tempera</p> ... Show More
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Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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Publication Date
Mon May 01 2017
Journal Name
Al-mustansiriyah Journal Of Science
Synthesis, characterization and antibacterial Evaluation for mixed-ligand Complexes of Nickle (II), Manganese (II), Copper (II), Cobalt (II) and Mercury (II) with Tetradentate
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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Mathematical Modeling of a Hollow Fiber Module Used in Pressure-Retarded Osmosis Process
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   Pressure retarded osmosis (PRO) can be considered as one of the methods for utilizing osmotic power, which is a membrane-based technology. Mathematical modeling plays an essential part in the development and optimization of PRO energy-generating systems. In this research, a mathematical model was developed for the hollow fiber module to predict the power density and the permeate water flux theoretically. Sodium chloride solution was employed as the feed and draw solution. Different operating parameters, draw solution concentration (1 and 2 M), the flow rate of draw solution (2, 3, and 4 L/min), and applied hydraulic pressure difference (0 - 90 bar) was used to evaluate the performance of PRO process of a hollow fiber module. The eff

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Publication Date
Tue Jul 01 2025
Journal Name
Iraqi Journal Of Architecture And Planning
Assessing the Influence of Urban Street Network on Land Use Distribution in Historic Urban Cores
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Prediction of the Effect of Using Stone Column in Clayey Soil on the Behavior of Circular Footing by ANN Model
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Shallow foundations are usually used for structures with light to moderate loads where the soil underneath can carry them. In some cases, soil strength and/or other properties are not adequate and require improvement using one of the ground improvement techniques. Stone column is one of the common improvement techniques in which a column of stone is installed vertically in clayey soils. Stone columns are usually used to increase soil strength and to accelerate soil consolidation by acting as vertical drains. Many researches have been done to estimate the behavior of the improved soil. However, none of them considered the effect of stone column geometry on the behavior of the circular footing. In this research, finite ele

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