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Data-Driven Damage Model Based on Nondestructive Evaluation
Journal article   Open access   Peer reviewed

Data-Driven Damage Model Based on Nondestructive Evaluation

Konstantinos P. Baxevanakis, Brian Wisner, Sara Schlenker, Harsh Baid and Antonios Kontsos
Journal of nondestructive evaluation, diagnostics and prognostics of engineering systems, v 1(3), pp 031007-031007-12
01 Aug 2018
DOI: https://doi.org/10.1115/1.4040040
url
https://digital.library.unt.edu/ark:/67531/metadc666897/View
SubmittedOpen Access (License Unspecified),  Open
url
https://doi.org/10.1115/1.4040040View
Published, Version of Record (VoR) Open

Abstract

remaining useful life acoustic emission data-driven model damage mechanics digital image correlation
A computational damage model, which is driven by material, mechanical behavior, and nondestructive evaluation (NDE) data, is presented in this study. To collect material and mechanical behavior damage data, an aerospace grade precipitate-hardened aluminum alloy was mechanically loaded under monotonic conditions inside a scanning electron microscope, while acoustic and optical methods were used to track the damage accumulation process. In addition, to obtain experimental information about damage accumulation at the laboratory scale, a set of cyclic loading experiments was completed using three-point bending specimens made out of the same aluminum alloy and by employing the same nondestructive methods. The ensemble of recorded data for both cases was then used in a postprocessing scheme based on outlier analysis to form damage progression curves, which were subsequently used as custom damage laws in finite element (FE) simulations. Specifically, a plasticity model coupled with stiffness degradation triggered by the experimentally defined damage curves was used in custom subroutines. The results highlight the effect of the data-driven damage model on the simulated mechanical response of the geometries considered and provide an information workflow that is capable of coupling experiments with simulations that can be used for remaining useful life (RUL) estimations.

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5 citations in Web of Science
9 citations in Scopus

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Engineering, Multidisciplinary
Instruments & Instrumentation
Materials Science, Characterization & Testing
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