30 citations · 74 across the 6 of their papers we have counts for
6 papers
Physics-Guided Continual Learning for Predicting Emerging Aqueous Organic Redox Flow Battery Material Performance
Yucheng Fu, Amanda Howard, Chao Zeng +3
Aqueous organic redox flow batteries (AORFBs) have gained popularity in renewable energy storage due to their low cost, environmental friendliness and scalability. The rapid discov…
Investigation of countercurrent flow profile and liquid holdup in random packed column with local CFD data
Yucheng Fu, Jie Bao, Rajesh Kumar Singh +2
Liquid holdup and mass transfer area are critical parameters for packed column design and CO2 capture efficiency prediction. In this paper, a framework was established for modeling…
Hydrodynamics of countercurrent flows in a structured packed column: effects of initial wetting and dynamic contact angle
Rajesh Kumar Singh, Jie Bao, Chao Wang +2
Computational countercurrent flow investigation in the structured packed column is a multiscale problem. Multiphase flow studies using volume of fluid (VOF) method in the represent…
Physics-informed machine learning of redox flow battery based on a two-dimensional unit cell model
Wenqian Chen, Yucheng Fu, Panos Stinis
In this paper, we present a physics-informed neural network (PINN) approach for predicting the performance of an all-vanadium redox flow battery, with its physics constraints enfor…
Scientific Computing Algorithms to Learn Enhanced Scalable Surrogates for Mesh Physics
Brian R. Bartoldson, Yeping Hu, Amar Saini +6
Data-driven modeling approaches can produce fast surrogates to study large-scale physics problems. Among them, graph neural networks (GNNs) that operate on mesh-based data are desi…
Latent Space Simulation for Carbon Capture Design Optimization
Brian Bartoldson, Rui Wang, Yucheng Fu +5
The CO2 capture efficiency in solvent-based carbon capture systems (CCSs) critically depends on the gas-solvent interfacial area (IA), making maximization of IA a foundational chal…