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

Abstract

Ductile 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 realworld 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.

New nanoscale toughening mechanisms mitigate embrittlement in binary nanocrystalline alloys

“…Two separate and independent Molecular Dynamics (MD) simulation approaches were employed to explore tensile behavior. Inspired by the blind independent comparative modeling employed in the Sandia Fracture Challenges, 49,50 these two independent MD models provide a rare example of prediction differences arising from differing assumptions and boundary conditions, providing for a more robust interpretation and comparison to experimental observations. The two independent modeling subteams, both with extensive expertise in MD modeling, had the same goal of replicating the experimental behavior, and a secondary outcome of the present study was to illustrate the breadth of differences and important similarities arising from two arguably valid approaches.…”

Data-Driven Materials Investigations: The Next Frontier in Understanding and Predicting Fatigue Behavior

“…An example of such a published materials data set is the UltraHigh Carbon Steel Micrograph DataBase (UHCSDB). 32 Second, the community should organize blind-prediction competitions to assess data-driven fatigue models, analogous to the Sandia Fracture Challenge 33,34 or the long-running organic crystal structure prediction blind tests. 35 Finally, the community should adopt data platforms such as Citrination, 36 Materials Commons, 37 and Materials Data Facility, 38 as these systems greatly facilitate data and model sharing, reproducibility of results, and reuse of code.…”

Thermodynamic theory of crystal plasticity: Formulation and application to polycrystal fcc copper

“…Although difficult, the topic continues to be one of high economic and strategic value requiring models which are dedicated to specific materials (Berdichevsky, 2019a). Due to cumulative history effects and structural evolution, quantifying the details of the dislocation (and deformation twinning) mediated plasticity will be critical in predicting the ductile based damage of materials (Boyce et al, 2014(Boyce et al, , 2016. Especially with regards to material damage, the ability to successfully predict when and where materials fail will require theories specified by material and properly account for energy and thermodynamic coupling between the different deformation mechanisms.…”