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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
Thu Jul 01 2021
Journal Name
Chemical Methodologies
Novel Synthesis of Some N-Hydroxy Phthalimide Derivatives with Investigation of Its Corrosion Inhibition for Carbon Steel in HCl Solution
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In the current study, new derivatives were synthesized by reaction of N-hydroxyphthalimide with chloro acetyl chloride in the presence of Et3N as a base to form 1,3-dioxoisoindolin-2-yl 2-chloroacetate (B1), which in turn enters several reactions with different amines where it interacts with primary amines to give 1,3-dioxoisoindolin-2-yl acetate derivatives (B2-B4) in basic medium, in the same way it interacts with these amines but with adding KNCS to form thiourea derivatives (B5-B7). It also reacts with diamines to give bis(azanediyl) derivatives (compounds B8-B10). The prepared derivatives were diagnosed using infrared FTIR and 1HNMR,13CNMR for some derivatives. Compounds B4, B5 and B9 were measured as corrosion inhibitors the inhibitio

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Publication Date
Sun Dec 07 2014
Journal Name
Baghdad Science Journal
A Study Of Corrosion Behavior Of Low Carbon Steel In Acidic And Basic Washing Water Of Crude Oil Solution At Different Temperatures
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The corrosion behavior of low carbon steel in washing water of crude oil solution has been studied potentiostatically at five temperatures in the range ( 303 –343 )K, at pH ( 4 ) and at pH (4,6,7,9,11 ) at (343K)..The corrosion potential shifted to more negative values with increasing temperature and the corrosion current density increased with increasing temperature, the corrosion current density (icorr) decreased with increasing pH in the rang ( 4 – 7 ) and it increased with increasing pH in the rang ( 9 – 11 ) at ( 343 K ), while the corrosion potential generally variation with increasing pH in the rang (4-11)at(343K. From the general results for this study can be seen that thermodynamic and kinetic function were

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Protection of Galvanized steel from corrosion in salt media using sulfur nanoparticles
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                The characteristics of sulfur nanoparticles were studied by using atomic force microscope (AFM) analysis. The atomic force microscope (AFM) measurements showed that the average size of sulfur nanoparticles synthesized using thiosulfate sodium solution through the extract of cucurbita pepo extra was 93.62 nm. Protecting galvanized steel from corrosion in salt media was achieved by using sulfur nanoparticles in different temperatures. The obtained data of thermodynamic in the presence of sulfur nanoparticles referred to high value as compares to counterpart in the absence of sulfur nanoparticles, the high inhibition efficiency (%IE) and corrosion resistance were at high temperature, the corrosion rate or weig

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Publication Date
Thu Mar 01 2018
Journal Name
International Journal Of Science And Nature
EXPERIMENTAL AND THEORETICAL STUDY OF 3-BENZYL -2- MERCAPTOQUINOIZOLINE-4(3H)-ONE (BMQ) AS AN INHIBITOR OF CARBON STEEL CORROSION IN ACIDIC MEDIA
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The inhibition of 3-Benzyl -2-mercaptoquinoizoline -4 (3H)-one (BMQ) on the corrosion of carbon steel in 0.5 M HCl studied by potentionstat polarization methods at 303–333 K. Results obtained show that BMQ act as inhibitor for carbon steel in HCl solution. The inhibition efficiency increase with increase in BMQ concentration. Activation parameters and Gibbs free energy for the adsorption process using Statistical Physics calculated and discussed. Quantum chemical calculations using DFT at the B3LYP/6-31G level of theory were used to calculate some electronic properties of the molecule to verify any correlation between the inhibitive effect and molecular structure of BMQ. The quantum calculations were proceeded to get data around correlati

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Publication Date
Wed Jan 15 2003
Journal Name
كلية الترا ث الجامعة
Estimating an Exponentiated Expanded Power Function Distribution Using an Artificial Intelligence Algorithm
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The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.

Publication Date
Thu Mar 01 2007
Journal Name
Al-khwarizmi Engineering Journal
The Inverse Solution Of Dexterous Robot By Using Neural Networks
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The inverse kinematics of redundant manipulators has infinite solutions by using conventional methods, so that, this work presents applicability of intelligent tool (artificial neural network ANN) for finding one desired solution from these solutions. The inverse analysis and trajectory planning of a three link redundant planar robot have been studied in this work using a proposed dual neural networks model (DNNM), which shows a predictable time decreasing in the training session. The effect of the number of the training sets on the DNNM output and the number of NN layers have been studied. Several trajectories have been implemented using point to point trajectory planning algorithm with DNNM and the result shows good accuracy of the end

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Tue Oct 07 2025
Journal Name
Iraqi Journal Of Science
Synthesis and characterization of some 2-sulphanyl benzimidazole derivatives and study of effect as corrosion inhibitors for carbon steel in sulfuric acid solution
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This research involves the synthesis of some sulphanyl benzimidazole derivatives (Ia-c), which were prepared from reaction of 2-mercaptobenzimidazole substituted benzyl halide, and structures were identified by spectral methods[FTIR, 1H-NMR and 13C-NMR].These compounds were investigated as corrosion inhibitors for carbon steel in 1M H2SO4 solution using weight loss, potentiostatic polarization methods; obtained results showed that the sulphanyl benzimidazole derivatives retard both cathodic and anodic reactions in acidic media, by virtue of adsorption on the carbon steel surface. This adsorption obeyed Langmuir’s adsorption isotherm. The inhibition efficiency of (Ia-c) ranging between (65-92) %. By using different Ib derivative conc

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
River Water Salinity Impact on Drinking Water Treatment Plant Performance Using Artificial neural network
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The river water salinity is a major concern in many countries, and salinity can be expressed as total dissolved solids. So, the water salinity impact of the river is one of the major factors effects of water quality. Tigris river water salinity increase with streamline and time due to the decrease in the river flow and dam construction from neighboring countries. The major objective of this research to developed salinity model to study the change of salinity and its impact on the Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda water treatment plant along Tigris River in Baghdad city using artificial neural network model (ANN). The parameter used in a model built is (Turbidity, Ec, T.s, S.s, and TDS in)

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Publication Date
Thu Sep 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Corrosion Inhibition of Steel Reinforcement in Concrete
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