121 citations · 330 across the 20 of their papers we have counts for
3 papers · 1 filter
Review: Artificial Intelligence for Liquid-Vapor Phase-Change Heat Transfer
Youngjoon Suh, Aparna Chandramowlishwaran, Yoonjin Won
Artificial intelligence (AI) is shifting the paradigm of two-phase heat transfer research. Recent innovations in AI and machine learning uniquely offer the potential for collecting…
Breaking Boundaries: Distributed Domain Decomposition with Scalable Physics-Informed Neural PDE Solvers
Arthur Feeney, Zitong Li, Ramin Bostanabad +1
Mosaic Flow is a novel domain decomposition method designed to scale physics-informed neural PDE solvers to large domains. Its unique approach leverages pre-trained networks on sma…
BubbleML: A Multi-Physics Dataset and Benchmarks for Machine Learning
Sheikh Md Shakeel Hassan, Arthur Feeney, Akash Dhruv +5
In the field of phase change phenomena, the lack of accessible and diverse datasets suitable for machine learning (ML) training poses a significant challenge. Existing experimental…