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On January 17 Johannes Främby, Department of Industrial and Materials Science at Chalmers University of Technology, defended his doctoral theses “Methods for efficient modelling of progressive failure in laminated fibre-reinforced composites" successfully and became a SAFER doctor. Johannes has been one of two Ph.D. students in the FFI-project 'Modelling crash behaviour in future lightweight composite vehicles'. The focus has been homogenisation of the micro behaviour in the composite material during crushing. The project is associated to SAFER’s research area Human body protection.

Congratulations Johannes, we wish you all the best as a SAFER doctor!

Abstract (link to the complete thesis below)
To meet increasing demands on reduced CO2 emissions, the automotive industry is currently very active in research to reduce vehicle weight by incorporating laminated composites (primarily carbon fibre-reinforced polymers) into structural components.

Historically, composite materials have mainly been used in the aerospace industry, whereby CAE-based design and development tools for composite structures have been developed primarily to the specific needs and requirements in this industry. In general, the crashworthiness of aerospace structures is only assessed to a small extent compared to that of automotive structures. Consequently, no suitable numerical simulation tools, capable of assessing the crashworthiness of composite automotive structures, have been developed.

The fracture process of laminated composites is more complicated than that of metals, the dominant class of materials used in automotive crash protection systems today. Thus, numerical models developed for metals cannot be used to accurately predict the crashworthiness of composite structures. Instead, high-fidelity models that can resolve the complicated fracture process must be used. However, these models require excessive computational times, making industrial crash simulations infeasible. It is therefore crucial to develop computationally efficient numerical tools, which are able to accurately predict the crashworthiness performance of composite structures.

In this thesis, I will present a route towards full-scale vehicle crash simulations using a computationally efficient adaptive method. The method is based on an equivalent single-layer shell model which, during the analysis, is adaptively transformed to a high-fidelity model in areas where higher accuracy is required. This way, the increased computational cost, associated with the analysis of progressive damage in laminated composites, can be limited both in time and to the pertinent areas of the model.

The adaptive modelling method can successfully reproduce the same level of accuracy as a high-fidelity model, at lower computational cost. Consequently, this method can help to enable computationally efficient crash simulations of laminated structures, which in the long run will allow composite materials to have a widespread use in future automotive vehicles.