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Neural Network Modeling of Cutting Force and Chip Thickness Ratio for Turning Aluminum Alloy 7075-T6
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The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. The inputs to all networks are cutting speed, depth of cut, and feed rate. All networks performances (outputs) for all machining force components (cutting force, passive force and feed force) showed perfect match with the experimental data and the calculated correlation coefficients were equal to one. The built network for the chip thickness ratio is giving correlation coefficient equal one too, when its output compared with the experimental results. These networks (models) are used to optimize the cutting parameters that produce the lowest machining force and chip thickness ratio. The models showed that the optimum machining force was (240.46 N) which can be produced when the cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.27 mm/rev). The proposed network for the chip thickness ratio showed that the minimum chip thickness is (1.21), which is at cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.17 mm/rev).

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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
Mon Jun 01 2015
Journal Name
Journal Of Engineering
Mechanical Properties Of AA 6061-T6 Aluminum Alloy Friction Stir Welds
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The different parameters  on  mechanical  and  microstructural  properties  of  aluminium  alloy  6061-T6 Friction  stir-welded  (FSW) joints  were investigated in the  present study. Different welded  specimens were produced by employing variable rotating  speeds and welding speeds. Tensile strength of the produced joints  was tested at room  temperature and the the effecincy was assessed, it was 75% of the base metal at rotational speed 1500 rpm and weld speed 50 mm/min. Hardness of various zones of FSW welds are presented and  analyzed by  means of  brinell hardness number . Besides to thess tests the bending properties  investigat

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Corrosion Resistance of Synergistic Welding Process of Aluminium Alloy 6061 T6 in Sea Water
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Abstract

 

This work involves studying corrosion resistance of AA 6061T6 butt welded joints using Two different welding processes, tungsten inert gas (TIG) and a solid state welding process known as friction stir welding, TIG welding process carried out by using Rolled sheet of thickness6mm to obtain a weld joint with dimension of (100, 50, 5) mm using ER4043 DE (Al Si5) as filler metal and argon as shielding gas, while Friction stir welding process carried out using CNC milling machine with a tool of rotational speed 1000 rpm and welding speed of 50mm/min to obtain the same butt joint dimensions. Also one of weld joint in the same dimensions subjected to synergistic weld

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Publication Date
Wed Jan 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Hot Press Bonding of Aluminum Alloy AA6061-T6 to Polyamide and Polyamide Composites
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Abstract<p>In this study, aluminum alloyAA6061-T6 was joined by a hot press process with three types of material; polyamide PA 6.6 (nylon), 1% carbon nanotube/PA6.6 and 30% carbon fiber/PA6.6 composites. Three parameters were considered in the hot pressing; temperature (180, 200 and 220°C), pressure (2, 3, 4, 5 and 6 bar) and time of pressing (1, 2, 3, 4 and 5 minutes for 200ºC, and 0.25, 0.5, 0.75, 1 and 1.25 minutes for220ºC). Applied pressure has great effect on shear strength of the joint, corresponding to bonding time and temperature. Maximum shear strength was 8.89MPa obtained for PA6.6 at bonding conditions of 4 bar, 220ºC and 0.75 minute. For 30% carbon fiber/PA6,6 shear recorded was</p> ... Show More
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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Modeling The Power Grid Network Of Iraq
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Recently, the theory of Complex Networks gives a modern insight into a variety of applications in our life. Complex Networks are used to form complex phenomena into graph-based models that include nodes and edges connecting them. This representation can be analyzed by using network metrics such as node degree, clustering coefficient, path length, closeness, betweenness, density, and diameter, to mention a few. The topology of the complex interconnections of power grids is considered one of the challenges that can be faced in terms of understanding and analyzing them. Therefore, some countries use Complex Networks concepts to model their power grid networks. In this work, the Iraqi Power Grid network (IPG) has been modeled, visua

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption
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A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

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Publication Date
Fri Dec 31 2021
Journal Name
Iraqi Journal Of Laser
Parametric Optimization for Fatigue Life of 6061-T6 Aluminum Thin Sheets Processed with High-Speed Laser Shock Peening
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Abstract: Aluminum alloys grade 6061-T6 are characterized by their excellent properties and processing characteristics which make them ideal for varieties of industrial applications under cyclic loading, aluminum alloys show less fatigue life than steel alloys of similar strength. In the current study, a nanosecond fiber laser of maximum pulse energy up to 9.9 mJ was used to apply laser shock peening process (LSP) on aluminum thin sheets to introduce residual stresses in order to enhance fatigue life under cyclic loading Box-Behnken design (BBD) based on the design of experiments (DOE) was employed in this study for experimental design data analysis, model building and optimization The effect of working parameters spot size (ω), scannin

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Publication Date
Wed May 01 2019
Journal Name
Journal Of Engineering
Optimization of Friction Stir Welding Process Parameters to joint 7075-T6 Aluminium Alloy by Utilizing Taguchi Technique
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In this study, a 3 mm thickness 7075-T6 aluminium alloy sheet was used in the friction stir welding process. Using the design of experiment to reduce the number of experiments and to obtain the optimum friction stir welding parameters by utilizing Taguchi technique based on the ultimate tensile test results. Orthogonal array of L9 (33) was used based on three numbers of the parameters and three levels for each parameter, where shoulder-workpiece interference depth (0.20, 0.25, and 0.3) mm, pin geometry (cylindrical thread flat end, cylindrical thread with 3 flat round end, cylindrical thread round end), and thread pitch (0.8, 1, and 1.2) mm) this technique executed by Minitab 17 software. The results showed th

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Effect of Al2O3 Particles and Precipitation Hardening on the Properties of Cast 332 Aluminum Alloy
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In this work, 332 Al alloy was prepared and reinforced with (0.5% and 1%) nano-Al2O3 particles. The prepared unreinforced and reinforced 332 Al alloy with nano-Al2O3 were solution heat treated (T6) at 510 ̊C and aged at 225 ̊C with different times (1, 3, and 5 h). Hardness test was performed on all the prepared alloys. All prepared alloys were dry slided under different applied loads (5, 10, 15, and 20 N) against steel counterface surface using pin on disk apparatus. The results showed that refinement effect was observed after addition of nano-Al2O3 particles and a change in silicon morphology after performing the solution heat treatment. The results also showed that har

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