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Regression Modeling of EDM Process for AISI D2 Tool Steel with RSM
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In this paper, Response Surface Method (RSM) is utilized to carry out an investigation of the impact of input parameters: electrode type (E.T.) [Gr, Cu and CuW], pulse duration of current (Ip), pulse duration on time (Ton), and pulse duration off time (Toff) on the surface finish in EDM operation. To approximate and concentrate the suggested second- order regression model is generally accepted for Surface Roughness Ra, a Central Composite Design (CCD) is utilized for evaluating the model constant coefficients of the input parameters on Surface Roughness (Ra). Examinations were performed on AISI D2 tool steel. The important coefficients are gotten by achieving successfully an Analysis of Variance (ANOVA) at the 5 % confidence interval. The outcomes discover that Surface Roughness (Ra) is much more impacted by E.T., Ton, Toff, Ip and little of their interactions action or influence. To predict the average Surface Roughness (Ra), a mathematical regression model was developed. Furthermore, for saving in time, the created model could be utilized for the choice of the high levels in the EDM procedure. The model adequacy was extremely agreeable as the constant Coefficient of Determination (R2) is observed to be 99.72% and adjusted R2-measurement (R2adj) 99.60%.

 

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Publication Date
Tue Oct 01 2019
Journal Name
2019 12th International Conference On Developments In Esystems Engineering (dese)
Structural Modeling of Cross-Frame Behavior in Steel Girder Bridges
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Publication Date
Tue Mar 19 2019
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Material Removal Rate and Temperature in Magnetic Abrasive Finishing Process for Stainless Steel 304
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The effect of the magnetic abrasive finishing (MAF) method on the temperature rise (TR), and material removal rate (MRR) has been investigated in this paper. Sixteen runs were to determine the optimum temperature in the contact area (between the abrasive powder and surface of workpiece) and the MRR according to Taguchi orthogonal array (OA). Four variable technological parameters (cutting speed, finishing time, working gap, and the current in the inductor) with four levels for each parameter were used, the matrix is known as a L16 (44) OA. The signal to noise ratio (S/N) ratio and analysis of the variance (ANOVA) were utilized to analyze the results using (MINITAB17) to find the optimum condition and identify the significant p

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
K-Nearest Neighbor Method with Principal Component Analysis for Functional Nonparametric Regression
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This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Effect Ti/AlTiN Multilayer Coating on the Crater Wear Process of Cutting Tool and Tribological Properties
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Tool wear is a major problem in machining operations because the resulting material loss gradually changes of the machine tool. There many factors may leads to material loss like; friction, corrosion, and also it’s happened by rubbing during machining processes between the work piece and the tool. Dimensional accuracy of the work piece, and also the surface finish will be reducing by tool wear. It can also increase cutting force. In this study, we focused on the effect of the coating process on crater wear problems. Crater wear is caused by the flow between the chip and the rake face of the tool, whereas flank wear is caused by the contact between the tool and the work piece. In reducing crater wear, aluminum titanium nitride (AlTiN) u

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Engineering And Applied Sciences
MODELING THE TRANSPORT OF CONTAMINANT BY WASHING PROCESS IN THE SANDY SOIL
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The aim of this study is modeling the transport of industrial wastewater in sandy soil by using finite element method. A washing technique was used to remove the industrial wastewater from the soil. The washing technique applied with an efficient hydraulic gradient to help in transport of contaminant mass by advection. Also, the mass transport equation used in modeling the transport of industrial wastewater from soil includes the sorption and chemical reactions. The sandy soil samples obtained from Al-Najaf Governorate/Iraq. The wastewater contaminant was obtained from Al- Musyiebelectricity power plant. The soil samples were synthetically contaminated with four percentages of 10, 20, 30 and 40% of the contaminant and these percentages calc

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Publication Date
Tue Sep 04 2018
Journal Name
Al-khwarizmi Engineering Journal
Study the Effect of Cutting Parameters on Temperature Distribution and Tool Life During Turning Stainless Steel 316L
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This paper is focused on studying the effect of cutting parameters (spindle speed, feed and depth of cut) on the response (temperature and tool life) during turning process. The inserts used in this study are carbide inserts coated with TiAlN (Titanum, Aluminium and Nitride) for machining a shaft of stainless steel 316L. Finite difference method was used to find the temperature distribution. The experimental results were done using infrared camera while the simulation process was performed using Matlab software package. The results showed that the  maximum difference between the experimental and simulation results was equal to 19.3 , so, a good agreement between the experimental and simulation results  was achieved. Tool life w

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Publication Date
Wed Apr 01 2020
Journal Name
Journal Of Construction Engineering And Management
Development of Assessment Tool for Workforce Sustainability
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Publication Date
Thu Dec 12 2013
Journal Name
Iraqi Journal Of Science
Determination of Optimum Mechanical Drilling Parameters for an Iraqi Field with Regression Model
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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Mathematical Modeling of a Hollow Fiber Module Used in Pressure-Retarded Osmosis Process
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   Pressure retarded osmosis (PRO) can be considered as one of the methods for utilizing osmotic power, which is a membrane-based technology. Mathematical modeling plays an essential part in the development and optimization of PRO energy-generating systems. In this research, a mathematical model was developed for the hollow fiber module to predict the power density and the permeate water flux theoretically. Sodium chloride solution was employed as the feed and draw solution. Different operating parameters, draw solution concentration (1 and 2 M), the flow rate of draw solution (2, 3, and 4 L/min), and applied hydraulic pressure difference (0 - 90 bar) was used to evaluate the performance of PRO process of a hollow fiber module. The eff

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

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