Mechanics Based Tomography (MBT): Validation using experimental data

Goenezen, Sevan; Kim, Baik Jin; Kotecha, Maulik; Luo, Ping; Hematiyan, M. R.

doi:10.1016/j.jmps.2020.104187

Cited by 7 publications

(1 citation statement)

References 17 publications

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“…Typical measured noise levels with a DIC system for large specimens are in the order of 1% based on our experience with basic experiments on rubber like specimens (Goenezen et al 23 ) with regular camera systems. In the following, we provide a few examples of DIC data acquisition for micro-scale sized region of interests, which are generally imaged with an optical microscope or a scanning electron microscope (SEM).…”

Section: Discussionmentioning

confidence: 99%

Identification of the 3D crystallographic orientation using 2D deformations

Goenezen

Kotecha

Reddy

2021

The Journal of Strain Analysis for Engineering Design

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Polycrystalline materials consist of grains (crystals) oriented at different angles resulting in a heterogeneous and anisotropic mechanical behavior at that micro-length scale. In this study, a novel method is proposed for the first time to determine the [Formula: see text] crystal orientations of grains in a [Formula: see text] domain, using solely [Formula: see text] deformation fields. The grain boundaries are assumed to be unknown and delineated from the reconstructed changes in the crystallographic orientation. Further, the constitutive equations that describe the mechanical behavior of the domain in [Formula: see text] under plane stress conditions are derived, assuming that the material is transversely isotropic in 3D. Finite element based algorithms are utilized to discretize the inverse problem. The in-house written inverse problem solver is coupled with Matlab-based optimization scripts to solve for the mechanical property distributions. The performance of this method is tested at different noise levels with synthetic displacements that were used as measured data. The reconstructions deteriorate as the noise level is increased. This work presents a first milestone in the verification of this novel technology with synthetic data.

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Section: Discussionmentioning

confidence: 99%