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.
In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and
... Show MoreThis research studied the relationship of patterns of investigator personality with the big five dimensions (Extraversion, stability, interoperability, openness, and personal benevolent), in facing the job stress with its resources(characteristics of the role, quality of work, organizational structure, work environment, organizational policies, social relations, and organizational processes) which the investigators exposed to it at the General Inspectors Offices.
The researcher derived the idea of research from the importance of the work of these offices in a confrontation of various cases of financial and administrative corruption in Iraq at the present time, since itis one of the most important in
... Show MoreGlobal warming has had considerable effects on vital ecosystems, which has also been caused by increased temperatures and CO2 that follow changes in different abiotic factors, which poses threats to mangrove forests environment. This research was conducted to examine the physiological and morphological characteristics of the Rhizophora apiculata mangrove regarding higher air temperature for the variety of tree species that respond to climate change. Seedlings were cultivated for three months in regulated growth chambers with three varying temperatures of 38°C, 21°C under CO2 at 450 ppm, and ambient CO2 concentration i.e., 450 ± 20 ppm under average temperature at 28°C as the control condition
... Show MoreThis work presents the modeling of the electrical response of monocrystalline photovoltaic module by using five parameters model based on manufacture data-sheet of a solar module that measured in stander test conditions (STC) at radiation 1000W/m² and cell temperature 25 . The model takes into account the series and parallel (shunt) resistance of the module. This paper considers the details of Matlab modeling of the solar module by a developed Simulink model using the basic equations, the first approach was to estimate the parameters: photocurrent Iph, saturation current Is, shunt resistance Rsh, series resistance Rs, ideality factor A at stander test condition (STC) by an ite
... Show MoreAn assembled pulsed Nd:YAG laser-robot system for spot welding similar and dissimilar metals is presented in this paper. The study evaluates the performance of this system through investigating the possibility and accuracy of executing laser spot welding of 0.2 mm in thickness stainless steel grade AISI302 to 0.5 mm in thickness low carbon steel grade AISI1008. The influence of laser beam parameters (peak power, pulse energy, pulse duration, repetition rate, and focal plane position on the final gained best results are evaluated. Enhancement of the experimental results was carried by a computational simulation using ANSYS FLUENT 6.3 package code.
A liquid-solid chromatography of Bovine Serum Albumin (BSA) on (diethylaminoethyl-cellulose) DEAE-cellulose adsorbent is worked experimentally, to study the effect of changing the influent concentration of (0.125, 0.25, 0.5, and 1 mg/ml) at constant volumetric flow rate Q=1ml/min. And the effect of changing the volumetric flow rate (1, 3, 5, and 10 ml/min) at constant influent concentration of Co=0.125mg/ml. By using a glass column of (1.5cm) I.D and (50cm) length, packed with adsorbent of DEAE-cellulose of height (7cm). The influent is introduced in to the column using peristaltic pump and the effluent concentration is investigated using UV-spectrophotometer at 30oC and 280nm wavelength. A spread (steeper) break-through curve is gained
... Show MoreRegression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well- Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution.
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