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Optimization of Wear Parameters in AISI 4340 Steel
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Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine the optimum levels of wear parameters. The results show that using the optimal parameter setting (load3, sliding speed1, and sliding distance2) a lower wear rate is achieved. The error between the predicted and experimental values is only 3.19%, so good agreement between the actual and predicted results is observed.

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Publication Date
Thu Dec 04 2014
Journal Name
Engineering And Technology Journal
Optimization of the Time Required for Determination of the Total Dissolved Salts in Soil ‫
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Publication Date
Tue Nov 01 2022
Journal Name
Aci Structural Journal
Stress at Ultimate in Internally Unbonded Steel Based on Genetic Expression Programming
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Publication Date
Sat Jun 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Phenyl Thiourea as Corrosion Inhibitor for Mild Steel in Strong Hydrochloric Acid
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The inhibitive action of Phenyl Thiourea (PTU) on the corrosion of mild steel in strong Hydrochloric acid, HCl, has been investigated by weight loss and potentiostatic polarization. The effect of PTU concentration, HCl concentration, and temperature on corrosion rate of mild steel were verified using 2 levels factorial design and surface response analysis through weight loss approach, while the electrochemical measurements were used to study the behavior of mild steel in 5-7N HCl at temperatures 30, 40 and 50 °C, in absence and presence of PTU. It was verified that all variables and their interaction were statistically significant. The adsorption of (PTU) is found to obey the Langmuir adsorption isotherm. The effect of temperature on th

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Publication Date
Thu Nov 29 2018
Journal Name
Al-khwarizmi Engineering Journal
Surface Roughness Prediction for Steel 304 In Edm Using Response Graph Modeling
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Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on

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Publication Date
Thu Sep 01 2011
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The accountancy Using of Gaols programming model to determine the optimal production mix
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The research aims to determine the mix of production optimization in the case of several conflicting objectives to be achieved at the same time, therefore, discussions dealt with the concept of programming goals and entrances to be resolved and dealt with the general formula for the programming model the goals and finally determine the mix of production optimization using a programming model targets to the default case.

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Mechanical Properties Investigation of Composite Material Under Different Parameters Variations
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         The main objective of this research is to design and select a composite plate to be used in fabricating wing skins of light unman air vehicle (UAV). The mechanical properties, weight and cost are the basis criteria of this selection. The fiber volume fraction, fillers and type of fiber with three levels for each were considered to optimize the composite plate selection. Finite element method was used to investigate the stress distribution on the wing at cruise flight condition in addition to estimate the maximum stress. An experiments plan has been designed to get the data on the basis of Taguchi technique. The most effective parameters at the process to be find out by employing L9

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Publication Date
Mon Dec 10 2018
Journal Name
Day 1 Mon, December 10, 2018
Wellbore Trajectory Optimization Using Rate of Penetration and Wellbore Stability Analysis
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Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

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Publication Date
Mon Dec 10 2018
Journal Name
Day 1 Mon, December 10, 2018
Wellbore Trajectory Optimization Using Rate of Penetration and Wellbore Stability Analysis
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Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Catalysts for money laundering and control by the banks / analytical study in the province of Arbil measures
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Receive money laundering phenomenon of interest to researchers and scholars on different intellectual orientation of economic or political or other, as this process is gaining paramount importance in light of business and increase the number of banks in the province of Kurdistan of Iraq and Erbil in particular and in the presence of openness developments chaotic economic and there are no factors encourage money laundering operation because of the presence of the hidden economy and the weakness of the banking and legal measures to combat them, and on this basis there is a need to examine money laundering operation in the province of Arbil, to indicate the presence or absence of a money laundering operation in working in the provin

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Publication Date
Sun Jun 30 2013
Journal Name
Al-khwarizmi Engineering Journal
Estimated Outlet Temperatures in Shell-and-Tube Heat Exchanger Using Artificial Neural Network Approach Based on Practical Data
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The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

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