Although Friction Stir Welding (FSW) is broadly invested in joining aluminum alloys, welding T-joint configurations display revealing challenges due to the interface’s intricate material flow and stress development. Defect formation, including voids and lack of fusion, as well as sudden response forces and residual stresses, can substantially undermine joint performance. This study presents an innovative three-dimensional finite element model to predict the coupled thermomechanical conditions experienced during the friction stir welding (FSW) of AA 6061-T6 lap T-joint design. The study identifies the geometrical parameters of the FSW tool, including shoulder and pin diameters, as well as pin form (cylindrical and tapered), as critical variables affecting thermal and mechanical outcomes. Three distinct tool geometries (T1, T2, T3) were evaluated to achieve the objectives of the current mission of FSW of the AA6061 lap T-joint. This work employs the Coupled Eulerian–Lagrangian (CEL) finite element modality to anticipate and analyze factors influencing the service life of the friction stir welded T-joint. Temperature, plastic strain, von Mises stress, defect type, and force feedback on the tool generated over the fabrication of the T-joint structure were recorded and studied. Alongside thermocouples, infrared cameras were employed to assess the temperature history to validate numerical results, and macrostructural micrographs were produced to identify the type of voids. The findings indicated that the CEL finite element model overestimates the temperature by a maximum of 7% for the T3 tool shape. The plastic strain was more pronounced on the advancing side than on the retreating side. The von Mises stress exhibited an M-shaped distribution, reaching a maximum value of 70 MPa for the T2 tool. The CEL model demonstrated notable ability in capturing the sort of void produced by three distinct tools.
This deals with estimation of Reliability function and one shape parameter (?) of two- parameters Burr – XII , when ?(shape parameter is known) (?=0.5,1,1.5) and also the initial values of (?=1), while different sample shze n= 10, 20, 30, 50) bare used. The results depend on empirical study through simulation experiments are applied to compare the four methods of estimation, as well as computing the reliability function . The results of Mean square error indicates that Jacknif estimator is better than other three estimators , for all sample size and parameter values
A fuzzy logic approach (FLA) application in the process of stud arc welding environment was implemented under the condition of fuzziness input data. This paper is composed of the background of FLA, related research work review and points for developing in stud welding manufacturing. Then, it investigates thecase of developingstud arc welding process on the controversial certaintyof available equipment and human skills.Five parameters (welding time, sheet thickness, type of coating, welding current and stud shape) were studied.A pair of parameter was selected asiteration whichis welding current and welding time and used fo
... Show MoreBackground: Tap waters play an important role in fulfilling the people needs for drinking and domestic purposes. Contaminate the tap water with different pollutants has become an issue of great concern for 90% of people who are depended on the tap water as the main source of drinking. Pollutants can make their way easily into the delivering pipes which suffer from the leaking resulting in decreasing the quality of water. Objective: Therefore, assess the water quality for drinking purpose by calculating the water quality index is an important tool to ascertain whether the water is suitable for human consumption or not. Methods: In the present work, the water quality of the Al-Salam, western region of Baghdad city, Iraq was investigated for 7
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreAs computers become part of our everyday life, more and more people are experiencing a
variety of ocular symptoms related to computer use. These include eyestrain, tired eyes, irritation,
redness, blurred vision, and double vision, collectively referred to as computer vision syndrome.
The effect of CVS to the body such as back and shoulder pain, wrist problem and neck pain.
Many risk factors are identified in this paper.
Primary prevention strategies have largely been confined to addressing environmental
exposure to ergonomic risk factors, since to date, no clear cause for this work-related neck pain
has been acknowledged. Today, millions of children use computers on a daily basis. Extensive
viewing of the compute
Abstract
To evaluate the effectiveness of Phenolic Compound of Salvia Frigida on induced atopic dermatitis (AD) of mice. Forty mice were included in the study, divided in to four groups (10 mice/group): apparently healthy, induced AD without treatment, induced AD treated with tacrolimus 0.1% ointment, and induced AD treated with Phenolic Compound of Salvia Frigida cream 5%. Examination of histopathology was done and skin homogenates levels also measured. Levels of WBC, Eosinophil, skin tissue homogenate of IL-13 and IL-4, serum IgE, and histopathological scores were significantly increased among induced non treated AD group in comparison with control group. Comparisons of non-treated induced AD
... Show MoreStrengthening of the existing structures is an important task that civil engineers continuously face. Compression members, especially columns, being the most important members of any structure, are the most important members to strengthen if the need ever arise. The method of strengthening compression members by direct wrapping by Carbon Fiber Reinforced Polymer (CFRP) was adopted in this research. Since the concrete material is a heterogeneous and complex in behavior, thus, the behavior of the confined compression members subjected to uniaxial stress is investigated by finite element (FE) models created using Abaqus CAE 2017 software. The aim of this research is to study experimentally and numerically, the beha
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Strengthening of the existing structures is an important task that civil engineers continuously face. Compression members, especially columns, being the most important members of any structure, are the most important members to strengthen if the need ever arise. The method of strengthening compression members by direct wrapping by Carbon Fiber Reinforced Polymer (CFRP) was adopted in this research. Since the concrete material is a heterogeneous and complex in behavior, thus, the behavior of the confined compression members subjected to uniaxial stress is investigated by finite element (FE) models created using Abaqus CAE 2017 software.
The aim of this research is to study experime
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