Publications

Oldfield, Ron A.; Kramer, Sharlotte L.; Rushdi, Ahmad R.; Acquesta, Erin A.; Emery, John M.; Kuberry, Paul A.; Ray, Jaideep R.; Ackerman, Sarah A.; Cyr, Eric C.; Saavedra, Gary J.; Hughes, Clayton H.; Cardwell, Suma G.; Smith, John D.

Abstract not provided.

Johnson, Kyle J.; Maestas, Demitri M.; Noell, Philip N.; Lim, Hojun L.; Emery, John M.; Smith, Matthew C.; Martinez, Carianne M.; Davis, Warren L.

Abstract not provided.

JOM

Bishop, Joseph E.; Emery, John M.; Battaile, Corbett C.; Littlewood, David J.; Baines, Andrew J.

Two fundamental approximations in macroscale solid-mechanics modeling are (1) the assumption of scale separation in homogenization theory and (2) the use of a macroscopic plasticity material model that represents, in a mean sense, the multitude of inelastic processes occurring at the microscale. With the goal of quantifying the errors induced by these approximations on engineering quantities of interest, we perform a set of direct numerical simulations (DNS) in which polycrystalline microstructures are embedded throughout a macroscale structure. The largest simulations model over 50,000 grains. The microstructure is idealized using a randomly close-packed Voronoi tessellation in which each polyhedral Voronoi cell represents a grain. An face centered cubic crystal-plasticity model is used to model the mechanical response of each grain. The overall grain structure is equiaxed, and each grain is randomly oriented with no overall texture. The detailed results from the DNS simulations are compared to results obtained from conventional macroscale simulations that use homogeneous isotropic plasticity models. The macroscale plasticity models are calibrated using a representative volume element of the idealized microstructure. Ultimately, we envision that DNS modeling will be used to gain new insights into the mechanics of material deformation and failure.

Battaile, Corbett C.; Mota, Alejandro M.; Lim, Hojun L.; Littlewood, David J.; Veilleux, Michael V.; Emery, John M.; Ostien, Jakob O.; Kalashnikova, Irina

Abstract not provided.

Foulk, James W.; Mota, Alejandro M.; Veilleux, Michael V.; Emery, John M.; Hansen, Glen H.; Salinger, Andrew G.

Abstract not provided.

Boyce, Brad B.; Foulk, James W.; Littlewood, David J.; Mota, Alejandro M.; Ostien, Jakob O.; Silling, Stewart A.; Spencer, Benjamin S.; Wellman, Gerald W.; Bishop, Joseph E.; Brown, Arthur B.; Córdova, Theresa E.; Cox, James C.; Crenshaw, Thomas B.; Dion, Kristin D.; Emery, John M.

Fracture or tearing of ductile metals is a pervasive engineering concern, yet accurate prediction of the critical conditions of fracture remains elusive. Sandia National Laboratories has been developing and implementing several new modeling methodologies to address problems in fracture, including both new physical models and new numerical schemes. The present study provides a double-blind quantitative assessment of several computational capabilities including tearing parameters embedded in a conventional finite element code, localization elements, extended finite elements (XFEM), and peridynamics. For this assessment, each of four teams reported blind predictions for three challenge problems spanning crack initiation and crack propagation. After predictions had been reported, the predictions were compared to experimentally observed behavior. The metal alloys for these three problems were aluminum alloy 2024-T3 and precipitation hardened stainless steel PH13-8Mo H950. The predictive accuracies of the various methods are demonstrated, and the potential sources of error are discussed.