3 papers
physics.flu-dyn2026
Physics-Informed Neural Networks for Depth-Averaged Avalanche Dynamics
Pradyumn Singh Sikarwar, Vishal Sharma, Gaurav Bhutani
Accurate prediction of avalanche motion is essential for hazard assessment in mountainous terrain. This study develops and evaluates a physics-informed neural network (PINN) framew…
cond-mat.soft2026
Physics-Informed Neural Networks for Depth-Averaged Granular Avalanche Dynamics on Curved Topography
Pujan Pranavkumar Purohit, Pradyumn Singh Sikarwar, Vishal Sharma +1
Physics-informed neural networks (PINNs) provide a mesh-free framework for solving governing equations, but their application to granular avalanche dynamics over curved terrain rem…
physics.flu-dyn2026
Transient Electrical Response Beyond Quasistatic Capacitance at Mechanically Excited Droplet--Dielectric Interfaces
Pramodt Srinivasula, Rameez Raja Khan, Diwakar Singh +1
Dynamic electrowetting of conducting droplets under mechanical deformation is conventionally modeled as a quasi-static variable-capacitance system, in which the electrical response…