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Development of Hybrid Intelligent Models for Prediction Machining Performance Measure in End Milling of Ti6Al4V Alloy with PVD Coated Tool under Dry Cutting Conditions
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Ti6Al4V alloy is widely used in aerospace and medical applications. It is classified as a difficult to machine material due to its low thermal conductivity and high chemical reactivity. In this study, hybrid intelligent models have been developed to predict surface roughness when end milling Ti6Al4V alloy with a Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) has been hybridized with two heuristic optimization techniques, namely: gravitational search algorithm (GSA) and genetic algorithm (GA). Taguchi method was used with an L27 orthogonal array to generate 27 experiment runs. Design expert software was used to do analysis of variances (ANOVA). The experimental data were divided randomly into three subsets for training, validation, and testing the developed hybrid intelligent model. ANOVA results revealed that feed rate is highly affected by the surface roughness followed by the depth of cut. One-way ANOVA, including a Post-Hoc test, was used to evaluate the performance of three developed models. The hybrid model of Artificial Neural Network-Gravitational Search Algorithm (ANN-GSA) has outperformed Artificial Neural Network (ANN) and Artificial Neural Network-Genetic Algorithm (ANN-GA) models. ANN-GSA achieved minimum testing mean square error of 7.41 × 10−13 and a maximum R-value of 1. Further, its convergence speed was faster than ANN-GA. GSA proved its ability to improve the performance of BPNN, which suffers from local minima problems.

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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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Publication Date
Fri May 21 2021
Journal Name
Transportation Infrastructure Geotechnology
Behavior of Floating Stone Columns and Development of Porewater Pressure Under Cyclic Loading
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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Development and Assessment of Feed Forward Back Propagation Neural Network Models to Predict Sunshine Duration
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         The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp

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Publication Date
Fri Jan 01 2016
Journal Name
Statistics And Its Interface
Search for risk haplotype segments with GWAS data by use of finite mixture models
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The region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled

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Publication Date
Fri Dec 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
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, bu

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Publication Date
Thu Mar 31 2022
Journal Name
Journal Of The College Of Education For Women
Characteristics of Rainfall in Dry and Wet Seasons in Iraq
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      This research aims at making a comparative survey between the dry season in (2017-2018) and the wet season (2018-2019) in Iraq concerning the variation of rainfall and pressure systems responsible for such a difference. In this paper, seven climatological stations have been selected: Mosul, Kirkuk, Khanaqin, Baghdad, Rutba, Diwaniyah and Basra. Results have shown that the first category of rainfall of the two seasons has recorded a higher number of rainy days in comparison with the second and third categories with a total of 274 day in a dry season and 403 day of a wet season. Further, the total amount of the annual continuous rain is higher than the total of thunderstorms in a dry season as well as in the

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Publication Date
Mon Jan 01 2018
Journal Name
Aip Conference Proceedings
The study of behavior titanium pure commercially coated with hydroxyapatite and zirconia
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Publication Date
Sat Nov 07 2020
Journal Name
Journal Of Advanced Research In Fluid Mechanics And Thermal Sciences
Fully Automated Measurement Setup for Photovoltaic Panel Performance Evaluation and Testing under LabVIEW Platform
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Photovoltaic (PV) devices are widely used renewable energy resources and have been increasingly manufactured by many firms and trademarks. This condition makes the selection of right product difficult and requires the development of a fast, accurate and easy setup that can be implemented to test available samples and select the cost effective, efficient, and reliable product for implementation. An automated test setup for PV panels using LabVIEW and several microcontroller-based embedded systems were designed, tested, and implemented. This PV testing system was fully automated, where the only human intervention required was the instalment of PV panel and set up of required testing conditions. The designed and implemented system was

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Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Engineering
Numerical and Experimental Investigations of the Effect of PVD and Vacuum Pressure on the Degree of Saturation
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    Soft clays are generally characterized by low shear strength, low permeability and high compressibility. An effective method to accelerate consolidation of such soils is to use vertical drains along with vacuum preloading to encourage radial flow of water.  In this research numerical modeling of prefabricated vertical drains with vacuum pressure was done to investigate the effect of using vertical drains together with vacuum pressure on the degree of saturation of fully and saturated-unsaturated soft soils.  Laboratory experiments were conducted by using a specially-designed large consolidometer cell where a central drain was installed and vacuum pressure was applied. All tests were conducted

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
The slenderness ratio effect on the response of closed-end pipe piles in liquefied and non-liquefied soil layers under coupled static-seismic loading
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Abstract<p>This study presents the findings of a 3D finite element modeling on the performance of a single pile under various slenderness ratios (25, 50, 75, 100). These percentages were assigned to cover the most commonly configuration used in such kind of piles. The effect of the soil condition (dry and saturated) on the pile response was also investigated. The pile was modeled as a linear elastic, the surrounded dry soil layers were simulated by adopting a modified Mohr-Coulomb model, and the saturated soil layers were simulated by the modified UBCSAND model. The soil-pile interaction was represented by interface elements with a reduction factor (R) of 0.6 in the loose sand layer and 0.7 in t</p> ... Show More
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