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
The research involves using phenol – formaldehyde (Novolak) resin as matrix for making composite material, while glass fiber type (E) was used as reinforcing materials. The specimen of the composite material is reinforced with (60%) ratio of glass fiber.
The impregnation method is used in test sample preparation, using molding by pressure presses.
All samples were exposure to (Co60) gamma rays of an average energy (2.5)Mev. The total doses were (208, 312 and 728) KGy.
The mechanical tests (bending, bending strength, shear force, impact strength and surface indentation) were performed on un irradiated and irrad
... Show MoreThe current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
... Show MoreAtenolol was used with povidone iodine to prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on reaction between atenolol and povidone iodine in an aqueous medium. Optimum parameters was studied to increase the sensitivity development of method. Calibration graph was linear in the range of 2-19 mmol/L for cell A and 5-19 mmol/L for cell B. Limit of detection 146.4848 ng/55 µL and 2.6600 µg/200 µL respectively to cell A and cell B. Correlation coefficient (r) 0.9957 for cell A and 0.9974 for cell. Relative standard deviation (RSD %) was lower than 1%, (n=8) for the determination of
... Show MoreNonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a
... Show MoreBackground: He-Ne laser (632.8 nm) pre-irradiation may lead to modulate the damaging effects of ionizing radiation and decreasing in radiation damage on cells, by the induction of antioxidant defence mechanisms and accelerated the repair.
Objective: To study the protection properties of He-Ne laser (632.8 nm) pre-irradiation against UV light (253.7 nm) damage on human lymphocyte blood cells and its DNA.
Subject & Methods: 27 samples were processed only for lymphocyte blood cells separation, while a 45 samples for the extracted DNA from lymphocyte. The total of 72 sampleswere employed to evaluate the influence of He-Ne laser pre- irradiation against UV-light.
Results: The results showed that He-Ne laser (632.8 nm) pre-irradia