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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 Dec 31 2000
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
The Influence of Temperature on Corrosion Inhibition of Carbon Steel in Air-Saturated 7NH3PO4 by Potassium Iodide
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Publication Date
Tue Sep 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Corrosion and Galvanic behavior of Copper, Carbon steel and Zinc Couples in (3.5 %wt) Nacl Solution
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The galvanic corrosion of the (Cu - Fe), (Cu - Zn) and (Fe - Zn) couples have been investigated in 3.5% NaCl solution, 40ºC, different velocities (Re = 5000, 10000 and 15000) and different area ratio’s of cathode to anode (AR= 0.5,1 and 2), by using commercial metal pipe (cylindrical tube).The Zero Resistance Ammeter has been used to measure the galvanic current (Ig) and galvanic potential (Eg) with time. The galvanic current density increases with increasing velocity (Re) and the area ratio (AR). The galvanic potential (Eg) is shifted to less negative with increasing velocity (Re) and the area ratio (AR). A statistical relations for the galvanic current density and galvanic potential as a function of (Re). and the area ratio had been

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Accounting Mining Data Using Neural Networks (Case study)
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Business organizations have faced many challenges in recent times, most important of which is information technology, because it is widely spread and easy to use. Its use has led to an increase in the amount of data that business organizations deal with an unprecedented manner. The amount of data available through the internet is a problem that many parties seek to find solutions for. Why is it available there in this huge amount randomly? Many expectations have revealed that in 2017, there will be devices connected to the internet estimated at three times the population of the Earth, and in 2015 more than one and a half billion gigabytes of data was transferred every minute globally. Thus, the so-called data mining emerged as a

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Publication Date
Thu May 12 2022
Journal Name
Journal Of Economics And Administrative Sciences
Nonparametric Estimator (Histogram) For Estimating Probability Density Function: Nonparametric Estimator (Histogram) For Estimating Probability Density Function
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 In this paper we introduce several estimators for Binwidth of histogram estimators' .We use simulation technique to compare these estimators .In most cases, the results proved that the rule of thumb estimator is better than other estimators.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
On Training Of Feed Forward Neural Networks
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In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.

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Publication Date
Wed Mar 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Expired Colxacillin, Amoxicillin, and Ceflaxin Drugs as Inhibitors for Low Carbon Steel Corrosion in Sodium Chloride
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The ability to inhibit corrosion of low carbon steel in a salt solution (3.5%NaCl) has been checked with three real expired drugs (Cloxacillin, Amoxicillin, Ceflaxin) with variable concentrations (0, 250, 500, 750) mg/L were examined in the weight loss. The inhibition efficiency of the Cloxacillin 750 mg/L showed the highest value (82.8125 %) and the best inhibitor of the rest of the antibiotics. The different concentrations of Cloxacillin drug (0, 250, 500, 750) mg/L and temperature (25, 35, 45, 55) oC were studied as variables with potentiodynamic polarization, Scanning Electron Microscopy (SEM) for surface morphology and electrochemical impedance spectroscopy (EIS) depending on current values and the resistance of charge to

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Publication Date
Thu Apr 25 2019
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
STUDY THE ANTIBACTERIAL ACTIVITY AND INHIBITION EFFECT OF REACTIVE RED (31) DYE FOR THE CORROSION OF CARBON STEEL IN CORROSIVE MEDIA: STUDY THE ANTIBACTERIAL ACTIVITY AND INHIBITION EFFECT OF REACTIVE RED (31) DYE FOR THE CORROSION OF CARBON STEEL IN CORROSIVE MEDIA
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The inhibitive action of Reactive Red (RR31) dye against corrosion of carbon steel in 1M acetic acid solution has been studied using gravimetric method at temperature ranged (288-318)K. The antibacterial activity for the different concentrations of RR31 dye against different bacterial species was studied. The experimental data indicates that this dye acts as a potential inhibitor for carbon-steel in acetic acid medium and the protection efficiency increase with increasing (RR31) dye. The adsorption of (RR31) dye on the carbon steel surface was found to follow Langmuir adsorption isotherm. Thermodynamic data for the adsorption process such as Gibbs free energy change ∆Gads, enthalpy change ∆Hads, and entropy change ∆Sads were estima

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Publication Date
Thu Mar 15 2018
Journal Name
Moroccan Journal Of Chemistry
Corrosion Protection of Carbon Steel in seawater by alumina nanoparticles with poly (acrylic acid) as charging agent
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Nanostructured Al2O3has been applied as a protective coating against corrosion of the carbon steel (C.S) in seawater environment (3.5% NaCl) at temperatures range (298-328)K. Aluminananoparticles were deposited on carbon steel substrates by cathodic electrophoretic deposition (EPD) with ethanol as suspension medium and poly(acrylic acid) (PAA) as polymeric charging agent. Meanwhile, thesurface morphology was examined using Atomic-force microscopy (AFM). The cross-section AFM showed that the particles sizes for the Al2O3 NPs is around 60-80 nm. The anticorrosion behaviour of coated C.S was investigated in 3.5% NaCl at temperature range 298-328 K by potentiodynamic polarization measurements. Results show that using PAA in suspension coat incr

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Publication Date
Tue Jul 01 2025
Journal Name
Russian Journal Of Physical Chemistry A
Electrochemical and Theoretical Study of the Corrosion Inhibition of Carbon Steel Using 3-Allyl-2-mercaptoquinazolin-4(3H)-one in an Acidic Environment
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This study investigates the corrosion inhibition performance of a newly synthesized quinazolinone derivative, AMQ, on mild steel in a hydrochloric acid medium. The inhibition efficiency was evaluated using potentiodynamic polarization at varying inhibitor concentrations (100–250 ppm) and temperatures (303– 333 K). The results showed that AMQ exhibited effective corrosion inhibition, with the highest efficiency of 74% observed at 250 ppm and 323 K. Density Functional Theory (DFT) calculations were conducted to study the electronic properties of AMQ and its adsorption behavior. The thermodynamic parameters, including activation energy, enthalpy, and Gibbs free energy, were calculated, indicating spontaneous adsorption of AMQ onto the meta

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