Modeling mechanical behavior of an additively manufactured metal structure with local texture variations: a study on model form error

Brown, Judith Alice; Bishop, Joseph E.

doi:10.1088/1361-651X/aaf107

Title: Modeling mechanical behavior of an additively manufactured metal structure with local texture variations: a study on model form error

Journal Article · Mon Jan 07 00:00:00 EST 2019 · Modelling and Simulation in Materials Science and Engineering

DOI:https://doi.org/10.1088/1361-651X/aaf107· OSTI ID:1492376

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

Here, the repetitive rapid solidification that occurs in metal additive manufacturing (AM) processes creates microstructures distinctly different from wrought materials. Local variability in AM microstructures (either by design or unintentional) raises questions as to how AM structures should be modeled at the part-scale to minimize modeling error. The key goal of this work is to demonstrate a posteriori error estimation applied to an AM part. It is assumed that the actual microstructure is unknown and an approximate, spatially uniform material model is used. Error bounds are calculated for many reference models based on AM microstructures with elongated grain morphology and localized or global fiber textures during a post-processing step. The current findings promote confidence that a posteriori model form error estimation could be used effectively in mechanical performance simulations of AM parts to quickly obtain quantitative error metrics between an approximate model result and many microstructure-based reference models. The a posteriori error estimation introduces significant time savings compared to computing the full reference model solutions. Tight bounds on model form error are obtained when texture variations in the reference models occur on large length scales. For materials with property variation at small length scales, multi-scale error estimation techniques are needed to properly account for the many interfaces present between areas with different properties.

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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:: 1492376

Report Number(s):: SAND-2018-13372J; 670518

Journal Information:: Modelling and Simulation in Materials Science and Engineering, Vol. 27, Issue 2; ISSN 0965-0393

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 2 works

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