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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 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Estimating of Pore Pressure Gradient in Lower Fars Formation
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In petroleum industry, the early knowledge of “pore pressure gradient” is the basis in well design and the extraction of these information is more direct when the pore pressure gradient is equal to normal gradient; however, this matter will be more complex if it deviate from that limit which is called “abnormal pore pressure”, if this variable does not put in consideration, then many drilling problems will occur might lead to entire hole loss. To estimate the pore pressure gradient there are several methods, in this study; Eaton method’s is selected to extract the underground pressure program using drilling data (normalized rate of penetration) and logs data (sonic and density log). The results shows that an abnormal high press

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Publication Date
Sun Jun 02 2019
Journal Name
Baghdad Science Journal
Estimating the Reliability Function of (2+1) Cascade Model
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This paper discusses reliability R of the (2+1) Cascade model of inverse Weibull distribution. Reliability is to be found when strength-stress distributed is inverse Weibull random variables with unknown scale parameter and known shape parameter. Six estimation methods (Maximum likelihood, Moment, Least Square, Weighted Least Square, Regression and Percentile) are used to estimate reliability. There is a comparison between six different estimation methods by the simulation study by MATLAB 2016, using two statistical criteria Mean square error and Mean Absolute Percentage Error, where it is found that best estimator between the six estimators is Maximum likelihood estimation method.

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Publication Date
Tue Sep 01 2020
Journal Name
Key Engineering Materials
Push-Out Test of Steel-Concrete-Steel Composite Section for Pre-Installation and Post-Installation Techniques of Shear Connectors
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Composite steel-concrete sections have a broad benefit through increasing structural strength as well as minimizing the self-loads. All past researches were concerned with pre-installed shear connectors (PRSC) in the manufacturing of composite sections. A new fabrication technique for steel-concrete-steel composite sections were presented in the current study by the post-installation shear connectors (POSC) passed-through an embedded polymerizing vinyl chloride (PVC) pipes. The performance of normal strength concrete prisms with a specified strength of 32 MPa connected to square steel tubes (SST) was investigated. Six specimens were fabricated in both methodologies, PRSC and POSC were experimentally tested by Push-out test. The spac

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Charge density distributions and electron scattering form factors of 19F, 27Al and 25Mg nuclei
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An effective two-body density operator for point nucleon system folded with two-body correlation functions, which take account of the effect of the strong short range repulsion and the strong tensor force in the nucleon-nucleon forces, is produced and used to derive an explicit form for ground state two-body charge density distributions (2BCDD's) and elastic electron scattering form factors F (q) for 19F, 27Al and 25Mg nuclei. It is found that the inclusion of the two-body short range correlations (SRC) has the feature of reducing the central part of the 2BCDD's significantly and increasing the tail part of them slightly, i.e. it tends to increase the probability of transferring the protons from the central region of the nucleus towards

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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
EFFECT OF STEEL FIBERS ADDITION ON THE BEHAVIOR OF HIGH STRENGTH CONCRETE CIRCULAR SHORT COLUMNS
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loaded reinforced concrete circular short columns. An experimental investigation into the behavior
of 24 short reinforced concrete columns with and without steel fibers was carried out. The columns
had a circular section (200 mm diameter and 900 mm long). Test variables include concrete
strength, spacing of spiral reinforcement, and inclusion of steel fibers. The axial stress and axial
strains were obtained and used to evaluate the effects of the presence of steel fibers. It was found
that the addition of steel fibers slightly improves the load carrying capacity of the tested columns
whereas it significantly enhances the ductility of these specimens. Test results also indicated that for
the same confinement parameter

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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Publication Date
Wed Nov 16 2016
Journal Name
Eurasip Journal On Wireless Communications And Networking
Evaluation of efficient vehicular ad hoc networks based on a maximum distance routing algorithm
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Traffic management at road intersections is a complex requirement that has been an important topic of research and discussion. Solutions have been primarily focused on using vehicular ad hoc networks (VANETs). Key issues in VANETs are high mobility, restriction of road setup, frequent topology variations, failed network links, and timely communication of data, which make the routing of packets to a particular destination problematic. To address these issues, a new dependable routing algorithm is proposed, which utilizes a wireless communication system between vehicles in urban vehicular networks. This routing is position-based, known as the maximum distance on-demand routing algorithm (MDORA). It aims to find an optimal route on a hop-by-ho

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Publication Date
Mon May 15 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Potentiostatic Study for the effect Of LAS on the Corrosion Of pure Zinc in 0.01 M HCl solutions
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   A potentiostatic study for the corrosion of pure zinc in 0.01 M HCl was achieved in absence and presence of (linear alkylbenzene solfonate LAS) detergents in a range of concentrations (0-50) mg/L. The electrochemical studies included anodic, cathodic polarization by using potentiostat over temperature rang (293- 323) K.     The mechanism of corrosion rate of pure zinc was suggested by evaluating of αa , αc , ba , bc , i0 , Rp and the kinetic parameters also calculated ( Ea , A) at the above temperature rang, The thermodynamic of corrosion, corrosion accelerating and corrosion  protecting were investigated by calculating  (∆G, ∆H and ∆s) values

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Studying the Effect of Water on Electrical Conductivity of Carbon Reinforced Aluminum Composite Material
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The aim of this study is to understand the effect of addition carbon types on aluminum electrical conductivity which used three fillers of carbon reinforced aluminum at different weight fractions. The experimental results showed that electrical conductivity of aluminum was decreased by the addition all carbon types, also at low weight fraction of carbon black; it reached (4.53S/cm), whereas it was appeared highly increasing for each carbon fiber and synthetic graphite. At (45%) weight fraction the electrical conductivity was decreased to (4.36Scm) and (4.27Scm) for each carbon fiber and synthetic graphite, respectively. While it was reached to maximum value with carbon black. Hybrid composites were investigated also; the results exhibit tha

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Publication Date
Sun Jun 05 2011
Journal Name
Baghdad Science Journal
Design and Construction of a Testing Platform and Estimating Attenuation Painting Reflectivity to Laser Beam
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The project has been described the design and construction of a reliable optical testing platform used for evaluate the reflectivity of metal surfaces treated with special paintings required for laser beam attenuation. The platform comprises an Nd-YAG laser system which has been designed and fabricated with specifications to be compatible with their corresponding in laser range finder transmitters used for various applications. The reflectivity of various attenuating paintings, at different detection angles, has been observed. Moreover, the variation of the reflected energy with painting type and metal type to be painted has been studied experimentally. Results illustrated the existence of a definite angle, at which the reflectivity was max

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