Critical mechanical properties and FEA simulation for crashworthiness assessment of a coarse-grained cast AM50 alloy

A coarse-grained AM50 alloy was used as a model alloy for investigation of constitutive behaviour, Charpy toughness and effect of stress state on deformation and failure of cast Mg alloys. The results provide critical mechanical properties of a cast AM50 alloy for crashworthiness assessment and development of finite element simulation techniques. For cast Mg alloys, the effect of strain rate and temperature is larger on tensile strength than on compressive strength because twinning is more extensive in compression than in tension. The effect of strain rate on compressive strength is negligible because twinning activity of the cast Mg alloy is dominant. The load vs. deflection of Charpy specimens were measured for modelling, and the effect of loading rate and temperature on load of Charpy specimens is very small because part of the specimen is in compression. The equivalent strain to fracture of the cylindrical round notched tension specimen decreases with increasing stress triaxiality; though for the flat-grooved plane strain specimen, the equivalent fracture strain remains constant over the range of stress triaxiality investigated. Because the two different specimen geometries give rise to different Lode angle values, the test results show that the Lode angle parameter is an important parameter for deformation and fracture of Mg alloys. Finite element simulations of loading of the cylindrical notched-tension and Charpy specimens were carried out using a Lode-angle dependent von Mises model, and were found to provide a reasonable description of the load–displacement curves measured in the tests. For the flat-grooved plane strain specimens, the computations under-predicted the force–displacement response measured

The second Sandia Fracture Challenge : predictions of ductile failure under quasi-static and moderate-rate dynamic loading

International audienceDuctile failure of structural metals is relevant to a wide range of engineering scenarios. Computational methods are employed to anticipate the critical conditions of failure, yet they sometimes provide inaccurate and misleading predictions. Challenge scenarios , such as the one presented in the current work, provide an opportunity to assess the blind, quantitative predictive ability of simulation methods against a previously unseen failure problem. Rather than evaluate the predictions of a single simulation approach, the Sandia Fracture Challenge relies on numerous volunteer teams with expertise in computational mechanics to apply a broad range of computational methods, numerical algorithms, and constitutive models to the challenge. This exercise is intended to evaluate the state of health of technologies available for failure prediction. In the first Sandia Fracture Challenge, a wide range of issues were raised in ductile failure modeling, including a lack of consistency in failure models, the importance of shear calibration data, and difficulties in quantifying the uncertainty of prediction [see Boyce et al. (Int J Fract 186:5–68, 2014) for details of these observations]. This second Sandia Fracture Challenge investigated the ductile rupture of a Ti–6Al–4V sheet under both quasi-static and modest-rate dynamic loading (failure in ∼0.1 s). Like the previous challenge, the sheet had an unusual arrangement of notches and holes that added geometric complexity and fostered a competition between tensile-and shear-dominated failure modes. The teams were asked to predict the fracture path and quantitative far-field failure metrics such as the peak force and displacement to cause crack initiation. Fourteen teams contributed blind predictions, and the experimental outcomes were quantified in three independent test labs. Additional shortcomings were revealed in this second challenge such as inconsistency in the application of appropriate boundary conditions, need for a thermomechanical treatment of the heat generation in the dynamic loading condition, and further difficulties in model calibration based on limited real-world engineering data. As with the prior challenge, this work not only documents the 'state-of-the-art' in computational failure prediction of ductile tearing scenarios , but also provides a detailed dataset for non-blind assessment of alternative methods