11 citations · 14 across the 7 of their papers we have counts for
3 papers · 1 filter
Physics-Aware Distillation of a Grid Foundation Model for Real-Time Edge Inference
Vlad Alexandru Sănduleac, Shahariya Rasheed Rayamarakkarveettil Puthanpurayil, Noman Khan +1
Grid foundation models (GridFMs) are graph transformers pretrained on a masked power-flow objective, and evaluate power flow orders of magnitude faster than an iterative solver. Th…
Acceleration of Modelling with Physics Informed Learning: Frameworks and Perspectives for Real-Time Control of Electrochemical Devices
Remus Teodorescu, Yusheng Zheng, Yi Zhuang +2
Electrochemical devices (batteries, fuel cells, and electrolyzers) are in full development, driven by the green energy transition. Their real-time control requires ms predictions i…
Physics-informed neural network surrogate modeling of single particle model for lithium-ion batteries
Yi Zhuang, Yusheng Zheng, Yunhong Che +1
Physics-based models play a key role in battery management, yet face challenges in real-time applications due to the high computational cost of solving coupled algebraic-partial di…