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alkej-115
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
Mon Apr 09 2018
Journal Name
Al-khwarizmi Engineering Journal
Creating Through Points in Linear Function with Parabolic Blends Path by Optimization Method
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The linear segment with parabolic blend (LSPB) trajectory deviates from the specified waypoints. It is restricted to that the acceleration must be sufficiently high. In this work, it is proposed to engage modified LSPB trajectory with particle swarm optimization (PSO) so as to create through points on the trajectory. The assumption of normal LSPB method that parabolic part is centered in time around waypoints is replaced by proposed coefficients for calculating the time duration of the linear part. These coefficients are functions of velocities between through points. The velocities are obtained by PSO so as to force the LSPB trajectory passing exactly through the specified path points. Also, relations for velocity correction and exact v

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Engineering
Application of Building Information Modeling (3D and 4D) in Construction Sector in Iraq
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ABSTRACT

Building Information Modeling (BIM) is becoming a great known established collaboration process in Architecture, Engineering, and Construction (AEC) industry. In various cases in many countries, potential benefits and competitive advantages have been reported. However, despite the potentials and benefits of BIM technologies, it is not applied in the construction sector in Iraq just like many other countries of the world.

The purpose of this research is to understand the uses and benefits of BIM for construction projects in Iraq. This purpose has been done by establishing a fr

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Publication Date
Mon Sep 14 2015
Journal Name
Day 2 Tue, September 15, 2015
Modeling and History Matching of a Fractured Reservoir in an Iraqi Oil Field
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Abstract<p>In recent years the interest in fractured reservoirs has grown. The awareness has increased analysis of the role played by fractures in petroleum reservoir production and recovery. Since most Iraqi reservoirs are fractured carbonate rocks. Much effort was devoted to well modeling of fractured reservoirs and the impacts on production. However, turning that modeling into field development decisions goes through reservoir simulation. Therefore accurate modeling is required for more viable economic decision. Iraqi mature field being used as our case study. The key point for developing the mature field is approving the reservoir model that going to be used for future predictions. This can </p> ... Show More
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Publication Date
Mon Dec 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Corrosion Inhibition of Galvanic Couple Copper Alloy/Mild Steel in Cooling Water System
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The driving idea for the present work was to combine the effect of polyvinyl alcohol (PVA) as corrosion inhibitor with the distance between the anodic and cathodic elements of the galvanic cell, beside their area ratio, in scope of synergistic suppression of galvanic corrosion on Cu/Fe model couple, using weight loss method. The performance affecting galvanic corrosion process has been tested for three major factors affect the process:
1. Four PVA inhibitor concentrations were selected to be (0, 1000, 4000 and 7000 ppm) in simulated cooling water.
2. Two cathode: anode area ratios as 1:1 and 2.4:1.
3. Two distances apart cathode – anode as 3 and 7 cm.
Maximum corrosion inhibition achieved was 86% which indicates that increa

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Corrosion Behavior of Nanocomposite Al-9 wt% Si Alloy Reinforced with Carbon Nanotubes
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An effort is made to study the effect of composite nanocoating using aluminum-9%wt silicon alloys reinforced with different percentage (0.5,1,2,4)wt.% of carbon nanotubes (CNTs) using  plasma spraying. The effect of this composite on corrosion behavior for AA6061-T6 by extrapolation Tafel test in sea water 3.5wt% NaCl was invested. Many specimens where prepared from AA6061-T6 by the dimension (15x15x3)mm as this first set up and other steps include coating process, X-ray diffraction and SEM examination .The results show the CNTs increase the corrosion rate of the nanocomposite coatings with increasing the weight percentage of CNTs within the Al-Si matrix. Al-9wt%Si coating layer itself has less corrosion rate if compared with both n

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Publication Date
Sat Aug 31 2019
Journal Name
Iraqi Journal Of Physics
The Q-switched Nd:YAG laser shock processing effects on mechanical properties of C86400 Cu-Zn alloy: Q-switched Nd:YAG laser shock processing effects on mechanical properties of C86400 Cu-Zn alloy
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The aim of this paper is to investigate the effects of Nd:YAG laser shock processing (LSP) on micro-hardness and surface roughness of 86400Cu-Zn alloy. X-ray fluorescence technique was used to analyze the chemical composition of this alloy. LSP treatment was performed with a Q-switched Nd: YAG laser with a wavelength of 1064 nm. The results show that laser shock processing can significantly increase. The micro-hardness and surface roughness of the LSP-treated sample. Vickers diamond indenter was used to measure the micro-hardness of all samples with different laser pulse energy and the different number of laser pulses. It is found that the metal hardness can be significantly increased to more than 80% by increasing the laser energy and t

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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network
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Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

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Publication Date
Wed Jan 01 2025
Journal Name
Smart Innovation, Systems And Technologies
The Effect of Bulgarian Bag Exercises to Develop Explosive Force, Characterized by Speed and Accuracy of the Spiking Performance of Volleyball Players
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The purpose of this study is to develop and assess the effectiveness of exercises using heavy and hanging ropes for handball players, focusing on enhancing specific physical abilities and shooting accuracy. The research addresses the gap in training methodologies by comparing the effects of heavy rope exercises versus hanging rope exercises. An experimental design was used in two equal groups, besides pre-testing and post-testing. The study involved 16 players from the School of Handball for the season 2022–2023. The sample included 14 players, who were then randomly divided into two experimental groups of 7 each. The first group performed heavy rope exercises, while hanging rope exercises were included in the plan of the second group. Th

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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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Publication Date
Thu Jan 01 2009
Journal Name
Computer And Information Science 2009
The Stochastic Network Calculus Methodology
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Home Computer and Information Science 2009 Chapter The Stochastic Network Calculus Methodology Deah J. Kadhim, Saba Q. Jobbar, Wei Liu & Wenqing Cheng Chapter 568 Accesses 1 Citations Part of the Studies in Computational Intelligence book series (SCI,volume 208) Abstract The stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. This paper advances the stochastic network calculus by deriving a network service curve, which expresses the service given to a flow by the network as a whole in terms of a probabilistic bound. The presented network service curve permits the calculation of statistical end-to-end delay and backlog bounds for broad

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