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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 Sep 01 2016
Journal Name
Journal Of Engineering
Calculating the Transport Density Index from Some of the Productivity Indicators for Railway Lines by Using Neural Networks
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The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

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Publication Date
Tue Mar 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
The Inhibition Effect of Peach Juice on Corrosion of Low Carbon Steel in Hydrochloric Acid at Different Temperatures
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The corrosion inhibition of low carbon steel in1N HCl solution in the presence of peach juice at temperature (30,40,50,and 60)°C at concentration ( 5, 10, 20, 30, 40and 50 cm3/L)were studied using weight loss and polarization techniques. Results show that the inhibition efficiency was increased with the increase of inhibitor concentration and increased with the increase of temperature up to 50ºC ,above 50ºC (i.e. at 60 ºC) the values of efficiency decreases. Activation parameters of the corrosion process such as activation energies, Ea, activation enthalpies, ΔH, and activation entropies, ΔS, were calculated. The adsorption of inhibitor follows Langmuir isotherm. Maximum inhibition efficiency obtained was a bout 91% at 50ºC in the

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Mechanical Engineering
Corrosion Resistance Enhancement for Low Carbon Steel by Gas Phase Coating
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Corrosion Resistance Enhancement for low carbon steel is very important to extend its life service, the coating process is one of the methods which can using to achieve this, and it's the most important in surface treatments to improve the properties of metals and alloys surfaces such as corrosion resistance. In this work, low carbon steel was nitrided and coated with nano zinc using gas phase coating technical, to enhance the resistance of corrosion. The process included adding two layers. The first, a nitride layer, was added by precipitating nitrogen (N) gas, and the second, a zinc (Zn) layer, was added by precipitating Zn. The process of precipitating was carried out at different periods (5, 10, and 15 minutes). Scan electron mi

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Publication Date
Wed Dec 10 2025
Journal Name
Diyala Journal Of Engineering Sciences
Frankincense Extract as Eco-Friendly Corrosion Inhibitor for Carbon Steel in 1M HCl Solution
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Steel corrosion in acidic environments is a critical industrial challenge, necessitating effective yet eco-friendly inhibitors. This study aims to address this problem by introducing a novel, green alternative: frankincense extract (FE). The distinctive contribution of this work lies in the comprehensive investigation of FE natural, sustainable, and economically viable resin as an effective corrosion inhibitor for carbon steel in 1 M HCl. The research employs an integrated methodology, including electrochemical techniques (potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS)), adsorption isotherm modeling, surface analysis (FT-IR and FESEM/EDX), and density functional theory (DFT) calculations. Key res

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Publication Date
Sat Mar 10 2012
Journal Name
الدنانير
Cryptography Using Artificial Neural Network
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

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Publication Date
Mon Sep 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
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

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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
Tue Jan 01 2019
Journal Name
Iraqi Journal Of Agricultural Sciences
A review: Behavior of pitting corrosion in manufacturing food equipment
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Publication Date
Sat Dec 14 2024
Journal Name
Iraqi Journal Of Industrial Research
Corrosion Behaviour, Kinetic and Thermodynamic Studies of Water Hyacinth Extract as a Corrosion Inhibitor for Low-Carbon Steel
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Corrosion inhibitors are widely used in industry to reduce the corrosion rate of metals and alloys. Corrosion inhibitors adsorb onto metallic surfaces and insulate them from deterioration. Plants abundant in nature offer a cost-effective replacement for toxic chemical inhibitors on the market. The current research used the potentiostatic polarization technique at room temperature to explore the inhibitory impact of water hyacinth extract on the corrosion of low-carbon steel specimens in a 3.5% NaCl solution. The Tafel curve was used to assess corrosion inhibition activity, with the best inhibition efficiency reaching 79.36% at a concentration of 200 ppm. Cyclic polarization indicated the type of corrosion was general corrosion. The

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Direction Finding Using GHA Neural Networks
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 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

 

 

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