@article{BoyceKramerBosiljevacetal., author = {Boyce, Brad L. and Kramer, Sharlotte L. B. and Bosiljevac, T. R. and Corona, Edmundo and Moore, J. A. and Elkhodary, Khalil and Simha, C. Hari Manoj and Williams, Bruce W. and Cerrone, Albert R. and Nonn, Aida and Hochhalter, Jacob D. and Bomarito, Geoffrey F. and Warner, James E. and Carter, Bruce J. and Warner, Derek H. and Ingraffea, Anthony R. and Zhang, T. and Fang, X. and Lua, Jim and Chiaruttini, Vincent and Maziere, Matthieu and Feld-Payet, Sylvia and Yastrebov, Vladislav A. and Besson, Jacques and Chaboche, Jean Louis and Lian, J. and Di, Y. and Wu, Bei and Novokshanov, Denis and Vajragupta, Napat and Kucharczyk, Pawel and Brinnel, Viktoria and Doebereiner, Benedikt and Muenstermann, Sebastian and Neilsen, Michael K. and Dion, Kristin and Karlson, Kyle N. and Foulk, James Wesley and Brown, Arthur A. and Veilleux, Michael G. and Bignell, John L. and Sanborn, Scott E. and Jones, Chris A. and Mattie, Patrick D. and Pack, Keunhwan and Wierzbicki, Tomasz and Chi, Sheng-Wei and Lin, S.-P. and Mahdavi, Ashkan and Predan, Jozef and Zadravec, Janko and Gross, Andrew J. and Ravi-Chandar, KRISHNASWAMY and Xue, Liang}, title = {The second Sandia Fracture Challenge: predictions of ductile failure under quasi-static and moderate-rate dynamic loading}, series = {International journal of fracture}, journal = {International journal of fracture}, number = {198, 1-2}, publisher = {Springer}, doi = {10.1007/s10704-016-0089-7}, pages = {5 -- 100}, 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 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.}, language = {en} } @article{KramerJonesMostafaetal., author = {Kramer, Sharlotte L. B. and Jones, Amanda and Mostafa, Ahmed and Ravaji, Babak and Tancogne-Dejean, Thomas and Roth, Christian C. and Nonn, Aida}, title = {The third Sandia fracture challenge: predictions of ductile fracture in additively manufactured metal}, series = {International Journal of Fracture}, volume = {218}, journal = {International Journal of Fracture}, publisher = {Springer Nature}, doi = {10.1007/s10704-019-00361-1}, pages = {5 -- 61}, abstract = {The Sandia Fracture Challenges provide a forum for the mechanics community to assess its ability to predict ductile fracture through a blind, round-robin format where mechanicians are challenged to predict the deformation and failure of an arbitrary geometry given experimental calibration data. The Third Challenge (SFC3) required participants to predict fracture in an additively manufactured (AM) 316L stainless steel bar containing through holes and internal cavities that could not have been conventionally machined. The volunteer participants were provided extensive data including tension and notched tensions tests of 316L specimens built on the same build-plate as the Challenge geometry, micro-CT scans of the Challenge specimens and geometric measurements of the feature based on the scans, electron backscatter diffraction (EBSD) information on grain texture, and post-test fractography of the calibration specimens. Surprisingly, the global behavior of the SFC3 geometry specimens had modest variability despite being made of AM metal, with all of the SFC3 geometry specimens failing under the same failure mode. This is attributed to the large stress concentrations from the holes overwhelming the stochastic local influence of the AM voids and surface roughness. The teams were asked to predict a number of quantities of interest in the response based on global and local measures that were compared to experimental data, based partly on Digital Image Correlation (DIC) measurements of surface displacements and strains, including predictions of variability in the resulting fracture response, as the basis for assessment of the predictive capabilities of the modeling and simulation strategies. Twenty-one teams submitted predictions obtained from a variety of methods: the finite element method (FEM) or the mesh-free, peridynamic method; solvers with explicit time integration, implicit time integration, or quasi-statics; fracture methods including element deletion, peridynamics with bond damage, XFEM, damage (stiffness degradation), and adaptive remeshing. These predictions utilized many different material models: plasticity models including J2 plasticity or Hill yield with isotropic hardening, mixed Swift-Voce hardening, kinematic hardening, or custom hardening curves; fracture criteria including GTN model, Hosford-Coulomb, triaxiality-dependent strain, critical fracture energy, damage-based model, critical void volume fraction, and Johnson-Cook model; and damage evolution models including damage accumulation and evolution, crack band model, fracture energy, displacement value threshold, incremental stress triaxiality, Cocks-Ashby void growth, and void nucleation, growth, and coalescence. Teams used various combinations of calibration data from tensile specimens, the notched tensile specimens, and literature data. A detailed comparison of results based of these different methods is presented in this paper to suggest a set of best practices for modeling ductile fracture in situations like the SFC3 AM-material problem. All blind predictions identified the nominal crack path and initiation location correctly. The SFC3 participants generally fared better in their global predictions of deformation and failure than the participants in the previous Challenges, suggesting the relative maturity of the models used and adoption of best practices from previous Challenges. This paper provides detailed analyses of the results, including discussion of the utility of the provided data, challenges of the experimental-numerical comparison, defects in the AM material, and human factors.}, language = {en} }