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Improving Press Bending Production Quality through Finite Element Simulation: Integration CAD and CAE Approach
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Efficient operations and output of outstanding quality distinguish superior manufacturing sectors. The manufacturing process production of bending sheet metal is a form of fabrication in the industry of manufacture in which the plate is bent using punches and dies to the angle of the work design. Product quality is influenced by plate material selection, which includes thickness, type, dimensions, and material. Because no prior research has concentrated on this methodology, this research aims to determine V-bending capacity limits utilizing the press bending method. The inquiry employed finite element analysis (FEA), along with Solidworks was the tool of choice to develop drawings of design and simulations. The ASTM E290 standard guides this study. The software in this package may combine CAD (Computer-Aided Design) and CAE (Computer-Aided Engineering) without requiring extra design applications. This study tested SPCC and SPHC plate materials with five thickness variations. The findings embrace the number of failure risks associated with press bending exhibited on the von Mises stress diagram, which is directly proportional to showing the thickness limit of each material type throughout the bending process. The study's findings lay the groundwork for improving manufacturing quality by lowering the number of faulty goods produced by trial and error. Because the maximum allowable die width is 12 mm, the thickness limit of the press bending process is 2 mm. However, due to the greater intensity of the SPCC material, it has a reduced defect rate compared to SPHC material.

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Publication Date
Fri Apr 04 2014
Journal Name
International Journal Of Sciences: Basic And Applied Research
Production of bioethanol from reed (Phragmitesaustralis)
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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Manufacturing electrolysis cell for hydrogen production
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Publication Date
Fri Dec 30 2022
Journal Name
Journal Of Mathematics
Estimation of Parameters of Finite Mixture of Rayleigh Distribution by the Expectation-Maximization Algorithm
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In the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T

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Publication Date
Thu Oct 20 2016
Journal Name
Sociological Methods & Research
Mean Monte Carlo Finite Difference Method for Random Sampling of a Nonlinear Epidemic System
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In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo

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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
Mon Oct 01 2012
Journal Name
Computers & Mathematics With Applications
Boundary element formulations for the numerical solution of two-dimensional diffusion problems with variable coefficients
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Publication Date
Sun Sep 06 2009
Journal Name
Baghdad Science Journal
Regeneration and Cormels Production of White Prosperity and Priscilla Gladiolus Varities In Vitro
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Plant regeneration and cormel production was carried out from callus cultures initiated from White Prosperity and Priscilla Gladiolus Varities. It is aimed to produce plants and cormels in vitro all year round. The study included many experiments, these were the effect of Naphthalene acetic acid (NAA) and Kinetin (Kin) interaction on callus initiation, effect of Benzyl adenine (BA) on shoot regeneration from callus culture, effect of NAA on rooting after 30, 40 and 50 days in culture. The role of the type of agricultural medium (Peat moss or river sand and their mixture on plantlets survival after weaning was studied. Results showed that the interaction between NAA and Kin induced callus on axillary bud explants. Callus was best ini

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Publication Date
Thu Mar 01 2018
Journal Name
Journal Of Engineering
Numerical Simulation of Thermal-Hydrodynamic Behavior within Solar Air Collector
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Solar collectors, in general, are utilized to convert the solar energy into heat energy, where it is employed to generate electricity. The non-concentrating solar collector with a circular shape was adopted in the present study. Ambient air is heated under a translucent roof where buoyant air is drawn from outside periphery towards the collector center (tower base). The present study is aimed to predict and visualize the thermal-hydrodynamic behavior for airflow under inclined roof of the solar air collector, SAC. Three-dimensional of the SAC model using the re-normalization group, RNG, k−ε turbulence viscus model is simulated. The simulation was carried out by using ANSYS-FLUENT 14.5. The simulation

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Publication Date
Sun Jul 01 2018
Journal Name
Journal Of Construction Engineering And Management
Measuring and Evaluating Safety Maturity of Construction Contractors: Multicriteria Decision-Making Approach
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