Abstract
Complex structural components made from 7xxx series alloys are usually manufactured through hot stamping due to their low ductility at room temperature. With the help of a custom-made induction heating system, experiments are performed on aluminum alloy 7075 in its W-temper. The comprehensive experimental program is executed comprising more than 100 specimens to characterize the plasticity and fracture response at temperatures ranging from 180 to 480 °C and strain rates ranging from 0.001 to 2/s. Stress states ranging from simple shear to biaxial tension are obtained through the use of planar shear specimens and tensile specimens with central holes and various notches. Based on the experimental results, an attempt is made to calibrate an enhanced Johnson-Cook type of constitutive model before employing an isotropic machine learning based constitutive model for hybrid experimental-numerical analysis of the fracture experiments. The extracted loading paths to fracture reveal a negative strain rate effect and a non-monotonic effect of temperature on the ductility of AA7075-W. An isotropic neural network based fracture initiation model is proposed, trained and validated to describe the onset of fracture across the range of stress states, strain rates and temperatures considered.
Published Version
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