2 papers
physics.comp-ph2026
Physics-informed Kolmogorov-Arnold networks (PIKANs) for noise-robust reconstruction of boiling heat flux from infrared measurements
Siavash Khodakarami, Parimala Vardhan Vydyula, Aniruddha Bora +2
Recovering a noise-amplified inverse quantity from corrupted boundary data is a recurring problem in physics-informed learning for real-world applications. Specifically, small pert…
cs.CV2026
VFNet: Multi-View Spatio-Temporal Model for Void Fraction Estimation in Gas-Liquid Two-Phase Flow
Md Adnan Faisal Hossain, Raghav Rajeev, Kumar Nishant +3
Void fraction, which quantifies the proportion of the fluid flow volume occupied by the gas phase, is a key parameter in the characterization of gas-liquid two-phase flow. Existing…