2 papers
physics.comp-ph2025
Real-time physics-informed reconstruction of transient fields using sensor guidance and higher-order time differentiation
Hong-Kyun Noh, Jeong-Hoon Park, Minseok Choi +1
This study proposes FTI-PBSM (Fixed-Time-Increment Physics-informed neural network-Based Surrogate Model), a novel physics-informed surrogate modeling framework designed for real-t…
physics.comp-ph2025
Physics-Informed Neural Network-Based Discovery of Hyperelastic Constitutive Models from Extremely Scarce Data
Hyeonbin Moon, Donggeun Park, Hanbin Cho +3
The discovery of constitutive models for hyperelastic materials is essential yet challenging due to their nonlinear behavior and the limited availability of experimental data. Trad…