DOE OSTI · 3385088
A data-driven quantification of damage evolution cause by voids in polycrystalline materials
Abstract
This is the presentation I will give at COMPLAS 2025 conference highlighting our latest advancements in integrating deep learning for for quantification of damage.
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Montes de Oca Zapiain, David [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)] (ORCID:0000000178900859), Aragon, Nicole [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)] (ORCID:0000000252190438), Lim, Hojun [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)] (ORCID:0000000309844712). 2025-09-01. A data-driven quantification of damage evolution cause by voids in polycrystalline materials. https://doi.org/10.2172/3385088
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