Material models used in structural finite element analysis (FEA) are often one of the key aspects that engineers need to describe very accurately. Particularly in applications involving high levels of plastic deformation combined with temperature and strain rate effects, the description of material behaviour by means of appropriately calibrated models and parameters is mandatory.
Since the calibration process can be equally challenging and time-consuming due to the high degree of freedom in parameter dispersion, an automated approach is best to obtain robust and reliable results. For this task an optimization strategy based on genetic algorithms executed with modeFRONTIER is coupled with the LS-DYNA implicit solver to find the best set of parameters to correctly reproduce the behaviour of a metallic material from quasi-static conditions up to high strain rate regimes.
Read the articleCASE STUDY
The Arvedi Group approached the University of Trieste to find a solution to the uneven distribution of material inside the hopper of their blast furnace in Trieste, Italy.
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CASE STUDY
The purpose of the case study was to implement a design methodology that used multi-disciplinary simulation and an automated process to analyse thousands of product configurations and highlight vehicle performance distributions in terms of handling, comfort, and cost. This approach ensures that the best solution is always selected.
mechanics modefrontier automotive optimization