3 citations · 6 across the 4 of their papers we have counts for
5 papers
EventFlow: Real-Time Neuromorphic Event-Driven Classification of Two-Phase Boiling Flow Regimes
Sanghyeon Chang, Srikar Arani, Nishant Sai Nuthalapati +7
Flow boiling is an efficient heat transfer mechanism capable of dissipating high heat loads with minimal temperature variation, making it an ideal thermal management method. Howeve…
Bubble2Heat: Optical to Thermal Inference in Pool Boiling Using Physics-encoded Generative AI
Qianxi Fu, Youngjoon Suh, Xiaojing Zhang +2
Phase change process plays a critical role in thermal management systems, yet quantitative characterization of multiphase heat transfer remains limited by the challenges of measuri…
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…
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…
Deep Vision-Inspired Bubble Dynamics on Hybrid Nanowires with Dual Wettability
Jonggyu Lee, Youngjoon Suh, Max Kuciej +3
The boiling efficacy is intrinsically tethered to trade-offs between the desire for bubble nucleation and necessity of vapor removal. The solution to these competing demands requir…