Experimental Analyses and Predictive Modelling of Ultrasonic Welding Parameters for Enhancing Smart Textile Fabrication.

This study aims to illustrate the design, fabrication, and optimisation of an ultrasonic welding (UW) machine to join copper wires with non-woven PVC textiles as smart textiles. The study explicitly evaluates UW parameters' impact on heat generation, joint strength, and electrical properties, with a comprehensive understanding of the process dynamics and developing a predictive model applicable to smart textiles. The methodological approach involved designing and manufacturing an ultrasonic piezoelectric transducer using ABAQUS finite element analyses (FEA) software and constructing a UW machine for the current purpose. The full factorial design (FFD) approach was employed in experiments to systematically assess the influence of welding time, welding pressure, and copper wire diameter on the produced joints. Experimental data were meticulously collected, and a backpropagation neural network (BPNN) model was constructed based on the analysis of these results. The results of the experimental investigation provided valuable insights into the UW process, elucidating the intricate relationship between welding parameters and heat generation, joint strength, and post-welding electrical properties of the copper wires. This dataset served as the basis for developing a neural network model, showcasing a high level of accuracy in predicting welding outcomes compared to the FFD model. The neural network model provides a valuable tool for controlling and optimising the UW process in the realm of smart textile production.

Improved corrosion resistance and mechanical properties of severely deformed ZM31 alloy.

The hexagonal close-packed (HCP) crystal structure of Mg alloys lead to poor formability as well as other undesirable mechanical behaviors in an otherwise highly sought-after alloy for commercial use. This study investigates the evolution of microstructure, texture, corrosion and mechanical behaviors in Mg-Zn-Mn (ZM31) alloy after processing using Equal Channel Angular Pressing (ECAP). Dynamic recrystallization was evident in the ECAP-processed samples, correlated with a substantial fiber structure, and resulted in the attainment of notable grain refinement and high lattice strain. Average grain sizes of 2.2 and 2 µm were achieved via 2 and 4-Pass Bc processing, respectively. This significant refinement yielded lower corrosion rates through enhancement of the thickness, coherency, and stability of formed protective oxide layers. The corrosion rate in the NaCl medium was substantially enhanced by 99.5% after four passes via route Bc. The recrystallized fine structure was found to have contributed to yield strength, ultimate strength, and microhardness improvements. Deformation enhanced yield and ultimate strengths by 132% and 64%, respectively. The distinctive grain refinement mechanism exhibited through the current ECAP procedure has potential to pave the way for novel and impactful utilizations of ZM31 in industries that demand exceptional mechanical and corrosion performance.