Existing and emerging methods in computational mechanics are rarely validated against problems with an unknown outcome. For this reason, Sandia National Laboratories, in partnership with US National Science Foundation and Naval Surface Warfare Center Carderock Division, launched a computational challenge in mid-summer, 2012. Researchers and engineers were invited to predict crack initiation and propagation in a simple but novel geometry fabricated from a common off-the-shelf commercial engineering alloy. The goal of this international Sandia Fracture Challenge was to benchmark the capabilities for the prediction of deformation and damage evolution associated with ductile tearing in structural metals, including physics models, computational methods, and numerical implementations currently available in the computational fracture community. Thirteen teams participated, reporting blind predictions for the outcome of the Challenge. The simulations and experiments were performed independently and kept confidential. The methods for fracture prediction taken by the thirteen teams ranged from very simple engineering calculations to complicated multiscale simulations. The wide variation in modeling results showed a striking lack of consistency across research groups in addressing problems of ductile fracture. While some methods were more successful than others, it is clear that the problem of ductile fracture prediction continues to be challenging. Specific areas of deficiency have been identified through this effort. Also, the effort has underscored the need for additional blind prediction-based assessments.

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 \(\sim \)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.

The objective of this study was to identify the microstructural mechanisms related to the high strength and ductile behavior of 2139-Al, and how dynamic conditions would affect the overall behavior of this alloy. Three interrelated approaches, which span a spectrum of spatial and temporal scales, were used: (i) The mechanical response was obtained using the split Hopkinson pressure bar, for strain-rates ranging from $1.0×10−3s$ to $1.0×104s−1$. (ii) First principles density functional theory calculations were undertaken to characterize the structure of the interface and to better understand the role played by Ag in promoting the formation of the $Ω$ phase for several $Ω-Al$ interface structures. (iii) A specialized microstructurally based finite element analysis and a dislocation-density based multiple-slip formulation that accounts for an explicit crystallographic and morphological representation of $Ω$ and $θ′$ precipitates and their rational orientation relations were conducted. The predictions from the microstructural finite element model indicated that the precipitates continue to harden and also act as physical barriers that impede the matrix from forming large connected zones of intense plastic strain. As the microstructural FE predictions indicated, and consistent with the experimental observations, the combined effects of $θ′$ and $Ω$, acting on different crystallographic orientations, enhance the strength and ductility, and reduce the susceptibility of 2139-Al to shear strain localization due to dynamic compressive loads.

Climate change education is crucial for fostering informed and engaged future generations. However, traditional pedagogies often fail to engage learners fully and provide real-world, experiential learning. This paper presents a novel approach to climate change education through a three-day virtual reality (VR) hackathon. The hackathon focused on four United Nations (UN) Sustainable Development Goals (SDGs)—Quality Education, Affordable and Clean Energy, Sustainable Cities and Communities, and Climate Action. Using VR technology and game design software, engineering students worked in teams. They competed against each other in designing immersive environments that demonstrated their understanding of these SDGs and climate change. Our goal was to encourage the development of empathy, education, and awareness around these critical global issues. The hackathon also integrated authentic assessments, mirroring real-world engineering tasks and providing a more practical and relevant learning experience. Our findings suggest that this VR hackathon has significantly enhanced students’ understanding of the SDGs and climate change issues, their competency with VR technologies, as well as their teamwork and problem-solving skills. This paper discusses the hackathon’s design, implementation, and outcomes, highlighting the potential of such innovative approaches in tackling climate change education and awareness.