Identification of ductile fracture model parameters for three ASTM structural steels using particle swarm optimization

A non-iterative parameter identification procedure for the non-local Gurson-Tvergaard-Needleman model based on standardized experiments

“…The parameters q 1 , q 2 are extracted from micromechanical unit cell calculations [25,27,28]. Mostly the seminal ones of Tvergaard and Needleman are applied (q 1 = 1.0, q 2 = 1.5) as can be seen in the compiled table of employed GTN parameters by [34]. The nucleation parameters ε n and s n can be determined from metallographic investigations of interrupted tests or partial unloading [29].…”

“…The nucleation parameters ε n and s n can be determined from metallographic investigations of interrupted tests or partial unloading [29]. Often, these values are set ad-hoc to ε n = 0.3 and s n = 0.1 (compare also the compilation of parameters in [34]). This choice is robust from a numerical point of view and related predictions yielded reasonable agreement with respective experiments.…”

“…1. This pragmatic choice corresponds to typical values, as can be found, e.g., in the collected parameter sets in [33,34,50].…”

“…In order to improve the predictions for the void coalescence stage, it was later proposed in several studies to calibrate the critical void volume fraction f c from notched tensile tests, see [7,29,30,31,32] and references therein. In several recent studies, all GTN parameters were calibrated with the help of notched tensile tests [33,34] or the Small-Punch Test [35,36] using generic optimization algorithms, with a certain grouping of the parameters with respect to their influence on certain regimes of the load-deflection curves [37]. A round-robin study [32], however, revealed problems on the reproducibility of the results and rather weak predictions of fracture tests if the GTN parameters are calibrated only from notched tensile tests.…”