Junction growth in ultrasonic spot welding and ultrasonic additive manufacturing
Source abstract
Abstract
Abstract The processes of ultrasonic spot welding and ultrasonic additive manufacturing are modelled by approximating the weld interface as rough metallic surfaces in sliding contact. It is assumed that bonding is due to athermal plastic deformation of surface asperities and the associated growth of metallic junctions along the weld interface. To link the process variables and the extent of junction growth, an expression for the real contact area at the weld interface is combined with process-specific frictional heating models developed here. The resulting framework is validated by comparing its predictions of the weld strength with data from the ultrasonic welding literature. The close agreement between the framework's predictions and the experimental data demonstrates that the surface asperities soften due to frictional heating, while acoustic softening effects are insignificant. The junction growth model is used to identify parameter sets for ultrasonic spot welding and ultrasonic additive manufacturing that maximize the weld strength while simultaneously minimizing the thermal excursion at the weld interface. It is found that in ultrasonic spot welding, certain processing conditions can cause interfacial melting, although melting is not required to form strong bonds. It is also shown that in ultrasonic additive manufacturing, the deposition rate is highest when the positions of the peak temperature and complete interfacial bonding coincide underneath the sonotrode. If the position of complete interfacial bonding leads the position of the peak temperature, there is excessive heating of the build, and the sonotrode velocity can be increased without degrading bond quality.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Welding Techniques Analysis · Mechanical stress and fatigue analysis · MXene and MAX Phase Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (100+)
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