IEEE

Physics-informed Neural Network Approach for Early Degradation Trajectory Prediction of Power Semiconductor Modules

Abstract: DC power cycling tests in semiconductor modules induces repetitive thermal-mechanical stresses that accumulate as fatigue over time. This paper proposes a physics-informed neural network ...
IEEE

Physics-Informed Neural Network-Based Open Set Classification of Neighboring Vehicle Motion for Decision-Making in Autonomous Driving

Abstract: In this paper, a method for inferring the motion intentions of a neighboring vehicle ahead of an ego vehicle using a physics-informed deep neural network-based open-set classification ...
AlphaGalileo

Physics-Informed AI for Subsurface Modeling: Bridging Emulsion Flooding and Carbon Storage

Omarkhan Samarkanov, Masoud Riazi School of Mining and Geosciences Presented at: 6th EAGE Global Energy Transition Conference & Exhibition (GET ...
Physics World

Physics-based battery model parameterization from impedance data

Join the audience for a live webinar at 3 p.m. GMT/10 a.m. EST on 21 January 2026 Discover the role of impedance analysis in advancing battery-model development ...