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Estimating Pitting Corrosion Depth and Density on Carbon Steel (C-4130) using Artificial Neural Networks
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The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be quite effective; the results were validated by the experimental agreement with those acquired from laboratory tests. Specifically, the correlation coefficient, R = 0.9944.

 

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Publication Date
Sun Nov 26 2017
Journal Name
Journal Of Engineering
Compression Index and Compression Ratio Prediction by Artificial Neural Networks
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Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

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Publication Date
Mon Mar 23 2020
Journal Name
Baghdad Science Journal
Role of Carbon Dioxide on the Corrosion of Carbon Steel Reinforcing Bar in Simulating Concrete Electrolyte
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The main factors that make it possible to get the corrosion of reinforcing steel in concrete are chloride ions and the absorption of carbon dioxide from the environment, and each of them works with a mechanism which destroys the stable immunity of rebar in the concrete. In this work the effect of carbon dioxide content in the artificial concrete solution on the corrosion behavior of carbon steel reinforcing bar (CSRB) was studied, potentiostatically using CO2 stream gas at 6 level of concentrations;  0.03 to 2.0  weight percent, and the effect of rising electrolyte temperature was also followed  in the range 20 to 50 C. Tafel plots and cyclic polarization procedures were obeyed to investigate the c

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Publication Date
Mon Mar 31 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Evaluation of Sodium Chloride and Acidity Effect on Corrosion of Buried Carbon Steel Pipeline in Iraqi Soil
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In this work, corrosion parameters were evaluated using potentiodynamic polarization curves. In order to determine corrosion parameters of potential and current density of the interesting metal, carbon steel, environmental conditions of external corrosion of buried carbon steel pipeline in Iraqi soil were prepared in the laboratory using simulated prepared conditions. Solutions of sodium chloride at different concentrations (300, 1100, 1900, 2700, and 3500 ppm) were used. pH of solution were acidic at pH =5, and alkaline at pH = 9. Laboratory conditions were similar to those of Iraqi soil where the pipelines were buried. Temperature was constant at 20 °C. Potentiodynamic polarization curves, of potential vs. log current density, were ob

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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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Publication Date
Tue Jun 03 2025
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Comparison of some artificial neural networks for graduate students
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Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

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Publication Date
Sat Dec 31 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Corrosion Inhibition of Carbon Steel in Hydrochloric Acid under Dynamic Conditions
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In this work, studying the effect of ethylenediamine as a corrosion inhibitor was investigated for carbon steel in aerated HCl solution in range of 0.1-1N under dynamic conditions, i.e., rotational velocity of 400–1200 rpm in the temperature range 35 – 65 ºC.  Weight loss method was employed in absence and presence of the inhibitor as an adsorption type in concentration range 1000 – 5000 ppm using rotating cylinder specimens. The experimental results showed that corrosion rate in absence and presence of inhibitor is increased with increasing temperature, rotational velocity and concentration of acid. It is decreased with increasing inhibitor concentration for the whole range of temperature, rotational velocity and concentrati

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Publication Date
Fri Mar 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Corrosion Inhibition of Low Carbon Steel in Different HCl Concentrations by Phenythiourea
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Phenylthiourea  (PHTU),was  tested  as  inhibitor for  the  corrosion  of  low  carbon  steel  in different  HCI  acid concentration by mass loss ,and polarization measurements .it was found that (PHTU) is a good inhibitor for the corrosion of low carbon steel in 1,3,and 5N HCI solution ,and its inhibition efficiency (0) increases with its concentration and attains approximately 97% at l g/I .polarization curves indicate that (PHTU) acts as an anodic type inhibitor .the inhibitor was adsorbed on the low carbon steel surface according to the Langmuir adsorption isotherm model. Results show that the rate of corrosion of low carbon steel increased with increasing temperature o

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Publication Date
Mon Dec 28 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Predicting the Sporting Achievement in the Pole Vault for Men Using Artificial Neural Networks
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The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t

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Publication Date
Sun Jun 01 2025
Journal Name
Results In Materials
Adsorption, thermodynamic and corrosion study of enalapril malate pharmaceutical drug as corrosion inhibitor for carbon steel in saline solution
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Unused and expired pharmaceutical drugs are a novel type of organic corrosion inhibitor. They are less expensive, more effective, and less harmful than conventional organic corrosion inhibitors. This study investigated the effects of concentration, adsorption mechanism and thermodynamic parameters of enalapril malate (ENAP) as a corrosion inhibitor for carbon steel in a saline solution (3.5 % NaCl). The polarization method was used to determine the corrosion rate and inhibition efficiency. Field emission scanning electron microscopy (FE-SEM) and atomic force spectroscopy (AFM) were used to investigate the surface morphology and topography of carbon steel after immersion in both uninhibited and inhibited media for 24 h. Fourier transform inf

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Galvanic Corrosion of Carbon Steel -Stainless Steel Couple in Sulfuric Acid under Flow Conditions
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Galvanic corrosion of stainless steel 316 (SS316) and carbon steel (CS) coupled in 5% wt/v sulfuric acid solution at agitation velocity was investigated. The galvanic behavior of coupled metals was also studied using zero resistance ammeter (ZRA) method. The effects of agitation velocity, temperature, and time on galvanic corrosion current and loss in weight of both metals in both free corrosion and galvanic corrosion were investigated. The trends of open circuit potential (OCP) of each metal and galvanic potential (Eg) of the couple were, also, determined. Results showed that SS316 was cathodic relative to CS in galvanic couple and its OCP was much more positive than that of CS for all investigated ranges of

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