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Meeting TMS Specialty Congress 2025
Symposium 8th World Congress on Integrated Computational Materials Engineering (ICME 2025)
Presentation Title Deep Learning-Based Platinum Particle Analysis for Corrosion Insights in BWR Systems
Author(s) Txai Sibley, Ryan Jacobs, Dane Morgan, Kevin Field, Elizabeth Holm
On-Site Speaker (Planned) Txai Sibley
Abstract Scope This research investigates the use of deep learning-based image analysis models to detect platinum particles on Boiling Water Reactor (BWR) system components. These platinum particles, added through noble metal chemical addition (NMCA), are essential for preventing stress corrosion cracking by controlling water chemistry, thereby extending the lifespan of reactor parts. The study utilizes a segmentation model trained on a limited set of images to analyze platinum particles on reactor surfaces. By linking microstructural attributes with electrochemical potential (ECP), we aim to better understand corrosion behaviors and refine NMCA effectiveness evaluation. This work lays the groundwork for improving segmentation accuracy, reducing data collection and annotation costs, and deepening our comprehension of how platinum particles influence BWR reactor performance.
Proceedings Inclusion? Undecided

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