Data-Driven Optimization of Interlocking Metasurface Design
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Engineering topics
Publications and source records attributed to Noell, Philip James.
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Corrosion challenges persist throughout SNL’s mission areas. The primary difficulty lies in the fact that corrosion typically manifests as isolated, rare events, making preemptive identification exceedingly difficult. Our current strategy for addressing corrosion issues, such as anomalies and SFIs, is similarly isolated and reactive. This method is costly, time-consuming, heavily dependent on a limited number of experts, and offers minimal understanding of the overall damage distribution within the stockpile. This technical challenge is not unique to corrosion but is also prevalent in other material aging phenomena, such as tin-whisker growth in lead-free solder and fatigue failure of springs.
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This is the poster I will present at the GRC Aqueous Corrosion meeting detailing our latest work on integrating Machine Learning into the Computational Calculations of Galvanic Corrosion