11 research outputs found
Optimization of Mechanical Properties of Friction Stir Spot Welded Joints for Dissimilar Aluminum Alloys (AA2024-T3 and AA 5754-H114)
Thermal Conductivity of Magnesium Alloys in the Temperature Range from −125 °C to 400 °C
Hardness and densification behaviour of copper and bronze powders compacted with uniaxial die and cold isostatic pressing proceses
In this study hardness and densification behaviour of copper and bronze powders under wet bag cold isostatic and uniaxial die pressing processes are examined. In uniaxial pressing the specimens were compacted up to a pressure of 800 MPa. Cold isostatic pressing (CIP) resulted in better densification for both of the studied powder materials. Attained densities were 94 % for copper and 82 % for bronze powders. In uniaxial die pressing greater pressurisation was needed to attain the same densification that obtained with CIP. The microhardness of both of the studied materials were measured before and after pressing processes. Higher pressure resulted in dislocation and strain hardening and increased hardness of powders
Comparative modeling of wire electrical discharge machining (WEDM) process using back propagation (BPN) and general regression neural networks (GRNN) [Primerjalno modeliranje elektroerozijske zicne obdelave (WEDM) z uporabo povratnosti (BPN) in spošne nevronske regresijske mreze (GRNN)]
The use of two neural networks techniques to model wire electrical discharge machining process (WEDM) is explored in this paper. Both the back-propagation (BPN) and General Regression Neural Networks (GRNN) are used to determine and compare the WEDM parameters with the features of the surface roughness. A comparison between the back-propagation and general regression neural networks in the modeling of the WEDM process is given. It is shown that both the back-propagation and general regression neural networks can model the WEDM process with reasonable accuracy. However, back propagation neural network has better learning ability for the wire electrical discharge machining process than the general regression neural network. Also, the back-propagation network has better generalization ability for the wire electrical discharge machining process than does the general regression neural network
Experimental and Numerical Modeling Studies on Production of Mg by Vacuum Silicothermic Reduction of CaO·MgO
Interdiffusion in the Mg-Al System and Intrinsic Diffusion in beta-Mg2Al3
Solid-to-solid diffusion couples were assembled and annealed to examine the diffusion between pure Mg (99.96 pct) and Al (99.999 pct). Diffusion anneals were carried out at 573 K, 623 K and 673 K (300 A degrees C, 350 A degrees C and 400 A degrees C) for 720, 360, and 240 hours, respectively. Optical and scanning electron microscopes were used to identify the formation of the intermetallic phases, gamma-Mg17Al12, and beta-Mg2Al3, as well as the absence of the epsilon-Mg23Al30 in the diffusion couples. The thicknesses of the gamma-Mg17Al12 and beta-Mg2Al3 phases were measured and the parabolic growth constants were calculated to determine the activation energies for growth. Concentration profiles were determined with electron microprobe analysis using pure elemental standards. Composition-dependent interdiffusion coefficients in Mg-solid solution, gamma-Mg17Al12, beta-Mg2Al3, and Al-solid solutions were calculated based on the Boltzmann-Matano analysis. Integrated and average effective interdiffusion coefficients for each phase were also calculated, and the magnitude was the highest for the beta-Mg2Al3 phase, followed by gamma-Mg17Al12, Al-solid solution, and Mg-solid solution. Intrinsic diffusion coefficients based on Huemann\u27s analysis (e.g., marker plane) were determined for the similar to Mg-62 at. pct Al in the beta-Mg2Al3 phase. Activation energies and the pre-exponential factors for the interdiffusion and intrinsic diffusion coefficients were calculated for the temperature range examined. The beta-Mg2Al3 phase was found to have the lowest activation energies for growth and interdiffusion among all four phases studied. At the marker location in the beta-Mg2Al3 phase, the intrinsic diffusion of Al was found to be faster than that of Mg. Extrapolations of the impurity diffusion coefficients in the terminal solid solutions were made and compared with the available self-diffusion and impurity diffusion data from the literature. Thermodynamic factor, tracer diffusion coefficients, and atomic mobilities at the marker plane composition were approximated using the available literature values of Mg activity in the beta-Mg2Al3 phase