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DOE OSTI · 3013209

Generative AI for Wind-Wave Inflows

Cortiella, Alex [National Renewable Energy Lab., Golden, CO (United States)]·Rybchuk, Alex [National Renewable Energy Lab., Golden, CO (United States)] (ORCID:0000000344333993)·Sallam, Omar [National Renewable Energy Lab., Golden, CO (United States)]·Glaws, Andrew [National Renewable Energy Lab., Golden, CO (United States)]·King, Ryan [National Renewable Energy Lab., Golden, CO (United States)]
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Abstract

Extreme wind-wave conditions can create dangerous or damaging environmental conditions for sea-based structures and watercrafts. However, the model of consistent, coupled wind-wave flow conditions is computational expensive, even for simple flow scenarios. This work examines the use of diffusion-based generative artificial intelligence tools to accelerate the generation of these two-phase flows and to characterize probabilities of various states to help with the generation of extreme patterns.

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17 WIND ENERGY97 MATHEMATICS AND COMPUTINGextreme patternsgenerative modelingwind-wave flow

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Cortiella, Alex [National Renewable Energy Lab., Golden, CO (United States)], Rybchuk, Alex [National Renewable Energy Lab., Golden, CO (United States)] (ORCID:0000000344333993), Sallam, Omar [National Renewable Energy Lab., Golden, CO (United States)], Glaws, Andrew [National Renewable Energy Lab., Golden, CO (United States)], King, Ryan [National Renewable Energy Lab., Golden, CO (United States)]. 2025-11-24. Generative AI for Wind-Wave Inflows. https://doi.org/10.2172/3013209

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