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Meeting	MS&T22: Materials Science & Technology
Symposium	Uncertainty Quantification in Data-Driven Materials and Process Design
Presentation Title	Uncertainty Quantification of a High-throughput Local Plasticity Test: Profilometry-based Indentation Plastometry of Al 7075 T6 Alloy
Author(s)	Aaron E. Tallman, Denny John, Tanaji Paul, Arvind Agarwal
On-Site Speaker (Planned)	Aaron E. Tallman
Abstract Scope	The quantification of spatially variable mechanical response in structural materials remains a challenge. Additive manufacturing methods result in increased spatial property variations—the effect of which on component performance is of key interest. To assist iterative design of additively manufactured prototypes, lower-cost benchtop test methods with high precision and accuracy will be necessary. Profilometry-based indentation plastometry (PIP) promises to improve upon the instrumented indentation test in terms of the measurement uncertainty. PIP uses an isotropic Voce hardening model and inverse numerical methods to identify plasticity parameters. To quantify the uncertainty of the PIP test, ninety-nine PIP tests are performed on prepared portions of an Al 7075 plate sample. The profilometry data and the Voce parameter predictions are examined to distinguish contributions of noise, individual measurement uncertainty, and additional set-wide variations. The quantification of material variability in the presence of measurement uncertainty is discussed.

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Uncertainty Quantification of a High-throughput Local Plasticity Test: Profilometry-based Indentation Plastometry of Al 7075 T6 Alloy

Uncertainty Quantification of Constitutive Models in Crystal Plasticity Finite Element Method

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