Direct numerical simulations in solid mechanics for quantifying the macroscale effects of microstructure and material model-form error

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

doi:10.1007/s11837-016-1857-6

Title: Direct numerical simulations in solid mechanics for quantifying the macroscale effects of microstructure and material model-form error

Journal Article · Wed Mar 16 00:00:00 EDT 2016 · JOM. Journal of the Minerals, Metals & Materials Society

DOI:https://doi.org/10.1007/s11837-016-1857-6· OSTI ID:1262246

^[1]; Emery, John M. ^[1]; Battaile, Corbett C. ^[1]; Littlewood, David J. ^[1]; Baines, Andrew J. ^[2]

Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
General Motors, Milford, MI (United States)

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. Furthermore, we envision that DNS modeling will be used to gain new insights into the mechanics of material deformation and failure.

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Research Organization:: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC04-94AL85000

OSTI ID:: 1262246

Report Number(s):: SAND-2016-2894J; PII: 1857

Journal Information:: JOM. Journal of the Minerals, Metals & Materials Society, Vol. 68, Issue 5; ISSN 1047-4838

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 15 works

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