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.
With the recent developments of technology and the advances in artificial intelligent and machine learning techniques, it becomes possible for the robot to acquire and show the emotions as a part of Human-Robot Interaction (HRI). An emotional robot can recognize the emotional states of humans so that it will be able to interact more naturally with its human counterpart in different environments. In this article, a survey on emotion recognition for HRI systems has been presented. The survey aims to achieve two objectives. Firstly, it aims to discuss the main challenges that face researchers when building emotional HRI systems. Secondly, it seeks to identify sensing channels that can be used to detect emotions and provides a literature review
... Show MoreIn oil and gas well cementing, a strong cement sheath is wanted to insure long-term safety of the wells. Successful completion of cementing job has become more complex, as drilling is being done in highly deviated and high pressure-high temperature wells. Use of nano materials in enhanced oil recovery, drilling fluid, oil well cementing and other applications is being investigated. This study is an attempt to investigate the effect of nano materials on oil well cement properties. Two types of nano materials were investigated, which are Nano silica (>40 nm) and Nano Alumina (80 nm) and high sulfate-resistant glass G cement is used. The investigated properties of oil well cement included compressive strength, thickening
... Show MoreMaintenance of machine tools can be improved significantly by analyzing the operating of manufacturing process with the real-time monitoring system for 3-D single point deformation measurements. Therefore, the process of manufacturing could be optimized with less cost. Recently, wireless technology and internet of things (IOT) applied on intelligent machine has witnessed a significant advance with augmented virtuality, the analysis and the process certainly would contribute to enhance the intelligence of that machine. This paper presents a group of the wireless sensors and 3D animation technologies for data monitoring and analyzing. Three degree of freedom robotic hand structure has been selected as a prototype to be form the process of the
... Show MoreIn this paper, An application of non-additive measures for re-evaluating the degree of importance of some student failure reasons has been discussed. We apply non-additive fuzzy integral model (Sugeno, Shilkret and Choquet) integrals for some expected factors which effect student examination performance for different students' cases.
We have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.
The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F
... Show MoreThe alluvial fan of Mandali located between latitude 30˚45’00” N longitude 45˚30’00” E in east of Diyala Governorate, Iraq. Thirty-five wells were identified in the study area with average depth of 84 m and estimated area of 21550 ha. A three-dimensional conceptual model was prepared by using GMS program. From wells cross sections, four geological layers have been identified. The hydraulic conductivity of these layers was calculated for steady state condition, where the water levels for nine wells distributed over the study area were observed at same time. Afterward, PEST facility in the GMS was used to estimate the aquifer hydraulic characteristics. Other characteristics such as storage coefficient and specific yield have
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The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (kLa), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w
... Show MoreThe objectives of this paper was the development of a novel ligand, L, which was achieved in two stages: ligand is synthesised by reducing the result of the reaction between cyclohexane-1,2-diamine and 4-hydroxy-3,5-dimethoxycy clohexane-1-carbaldehyde, followed by the production of the 4,4’-((1E,1’E)-(1,2 phenylenebis(azanylylidene))bis(methanylylidene))bis(2,6-dimethoxyphenol) precursor (P). While studying corrosion inhibition (copper alloy) in acid solution by weight loss, compounds were characterised using 1H, 13CNMR (for ligand (L) and (P)), FT-IR and UV spectra, melting point, molar conductivity, %C, %H and %N, %M, and magnetic susceptibility. The complex’s octahedral structure is inferred from the bidentate coordination
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