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Experimental investigation and modelling of residual stresses in face milling of Al-6061-T3 using neural network
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Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, but few of them provided the distribution of RS in a direct and singular way. This work focuses on studying and optimizing the effect of cutting speed, feed rate, and depth of cut for 6061-T3 aluminum alloy on the RS of the surface. The optimum values of geometry parameters have been found by using the L27 orthogonal array. Analysis and simulation of RS by using an artificial neural network (ANN) were carried out to predict the RS behavior due to changing machining process parameters. Using ANN to predict the behavior of RS due to changing machining process parameters is presented as a promising method. The milling process produces more RS at high cutting speed, roughly intermediate feed rate, and deeper cut, according to the results. The best residual stress obtained from ANN is ‒135.204 N/mm2 at a cutting depth of 5 mm, feed rate of 0.25 mm/rev and cutting speed of 1,000 rpm. ANN can be considered a powerful tool for estimating residual stress

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Investigation of the optimum cutting conditions during turning aluminum alloy using Taguchi method
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Publication Date
Sat Oct 09 2021
Journal Name
Nanomaterials
Investigation of Heat Transfer Enhancement in a Triple Tube Latent Heat Storage System Using Circular Fins with Inline and Staggered Arrangements
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Inherent fluctuations in the availability of energy from renewables, particularly solar, remain a substantial impediment to their widespread deployment worldwide. Employing phase-change materials (PCMs) as media, saving energy for later consumption, offers a promising solution for overcoming the problem. However, the heat conductivities of most PCMs are limited, which severely limits the energy storage potential of these materials. This study suggests employing circular fins with staggered distribution to achieve improved thermal response rates of PCM in a vertical triple-tube heat exchanger involving two opposite flow streams of the heat-transfer fluid (HTF). Since heat diffusion is not the same at various portions of the PCM unit,

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
An Investigation into Heat Transfer Enhancement by Using Oscillating Fins
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The present work describes numerical and experimental investigation of the heat transfer characteristics in a plate-fin, having built-in piezoelectric actuator mounted on the base plate (substrate). The geometrical configuration considered in the present work is representative of a single element of the plate-fin and triple fins. Air is taken as the working fluid. A performance data for a single rectangular fin and triple fins are provided for different frequency levels (5, 30 and
50HZ) , different input power (5,10,20,30,40 and 50W) and different inlet velocity (0.5, 1, 2, 3, 4, 5 and 6m/s) for the single rectangular fin and triple fins with and without oscillation. The investigation was also performed with different geometrical fin

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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
Thu Jul 01 2021
Journal Name
Energy
Experimental investigations of the performance of a flat-plate solar collector using carbon and metal oxides based nanofluids
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Publication Date
Sat May 14 2022
Journal Name
Oral And Maxillofacial Surgery
Evaluation of crestal sinus floor elevations using versah burs with simultaneous implant placement, at residual bone height ≥ 2.0 _ < 6.0 mm. A prospective clinical study
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Publication Date
Sat Aug 09 2025
Journal Name
مجلة العصر للعلوم الانسانية والاجتماع
Using Geographic Information Systems (GIS) to Determine the Optimal Site for a Landfill in Al-Nasr and Al-Salam Subdistrict
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This study addresses the selection of the optimal site for establishing a waste landfill within the study area by utilizing Geographic Information Systems (GIS) techniques integrated with the Analytic Hierarchy Process (AHP) methodology and the Weighted Overlay tool for multi-criteria spatial analysis. Six key criteria influencing site suitability were identified, including distance from urban areas, agricultural lands, irrigation canals, roads, villages, and barren (uncultivated and uninhabited) areas, with a focus on potential environmental and health impacts. The results indicate that ideal landfill sites are located at distances exceeding 800 to 1000 meters from agricultural and urban areas, providing effective protection to soil and gr

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Publication Date
Sat Aug 01 2020
Journal Name
Journal Of Engineering
Experimental Evaluation of Evaporative Cooling for Enhancing Photovoltaic Panels Efficiency Using Underground Water
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This paper presents an experimental study of cooling photovoltaic (PV) panels using evaporative cooling. Underground (geothermal energy) water used to extract heat from it during cooling and cleaning of PV panels. An experimental test rig was constructed and tested under hot and dusty climate conditions in Baghdad. An active cooling system was used with auxiliary an underground water tank to provide cold water as a coolant over both PV surfaces to reduce its temperature. The cellulose pad has been arranged on the back surface and sprays cooling on the front side. Two identical PV panels modules used: without cooling and evaporative water cooling. The experiments are comprised of four cases: Case (I): backside cooling, Ca

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Publication Date
Mon May 01 2023
Journal Name
Journal Of Engineering
Experimental Evaluation of PV Panel Efficiency Using Evaporative Cooling Integrated with Water Spraying
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In this work, an inventive photovoltaic evaporative cooling (PV/EC) hybrid system was constructed and experimentally investigated. The PV/EC hybrid system has the prosperous advantage of producing electrical energy and cooling the PV panel besides providing cooled-humid air. Two cooling techniques were utilized: backside evaporative cooling (case #1) and combined backside evaporative cooling with a front-side water spray technique (case #2). The water spraying on the front side of the PV panel is intermittent to minimize water and power consumption depending on the PV panel temperature. In addition, two pad thicknesses of 5 cm and 10 cm were investigated at three different water flow rates of 1, 2, and 3 lpm. In Case #1,

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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