Joining is a critical part of any structure for transferring load and maintaining integrity for the product. Ultrasonic weld is one of the popular methods for joining plastic parts in automotive industry. Along with providing a visually demanding finish, the method has been established for tight, strong, and dimensionally accurate joints. With the increase of complexity and integration of electrical and sensing instrumentation in autonomous and electric vehicles, sonic weld provides a necessary means of attaching plastic parts without compromising visual impact. However, the sonic weld performance is yet to be quantified, and the criteria for capturing weld separation, and losing this connected load path during structural vehicle analysis, has not been studied extensively. Sonic welds, even though it is a very effective joining method, the whole tooling process is expensive and time consuming. Ideally, to optimize the welding spot number and develop future cost-effective welding methods, it is crucial to understand the actual weld performance under several variables such as material type, temperature, strain rates, etc.
The strength of glass has been a subject of great interest for more than one hundred years. Due to the stochastic nature of glass, originating from microscopical surface flaws, glass plates exhibit large variations in fracture strength. The aim of this work is to present a new strength prediction model for glass, named the Glass Strength Prediction Model (GSPM) that captures the nature of fracture initiation in glass, spanning from rate dependence to size effects. We aim for the presented model to be applicable in modern design processes and provide a procedure to facilitate input parameter calibration for glass plates from different suppliers. GSPM is a Monte-Carlo based model that combines the theories of linear elastic fracture mechanics (LEFM) and sub-critical crack growth (SCG) to generate virtual tests on a representative sample of glass plates. The stress evolution in the glass plates is obtained from finite element (FE) simulations. The model results in representative fracture strength distributions that span the probable fracture initiation instances with respect to time, location and stress level. We demonstrate how the GSPM can be used to trigger fracture in the constitutive model MAT_280 in LS-DYNA. This feature provides the option to investigate scenarios including multiple glass plates with interdependent fracture initiation behavior. The GSPM displays great promise in terms of usability and prediction capacity. It can capture the fracture initiation behavior of glass plates of varying geometries exposed to load cases spanning from, e.g., quasi-static four-point bending to blast pressure. The model has the potential to reduce the number of physical experiments and numerical FE simulations in modern development processes of glass structures.
Viscoelastic behaviour of a material is often used as a probe in the field of material science since it is sensitive to the material’s chemistry and microstructure. The behaviour enables understanding of the quantity of energy absorbed by the material’s internal structure and the energy dissipated to the surroundings. The viscoelastic properties can be determined experimentally by tests such as stress relaxation, creep, or Dynamic Mechanical Analysis (DMA).
Sonic weld characterization and FEA modeling method development for automotive applications