A Non-Diffusive Neural Network Method for Solving Hyperbolic Conservation Laws
20 Sept 2025
Shocks, Collisions, and Entropy—Neural Networks Handle It All
20 Sept 2025
AI-driven PINNs simulate shock waves, collisions, and entropy solutions—advancing fluid dynamics beyond traditional models.
AI Learns to Predict Shock Waves
20 Sept 2025
Neural networks show promise in solving fluid dynamics problems, from shock waves to Euler’s equations, with surprising accuracy.
How Scientists Taught AI to Handle Shock Waves
20 Sept 2025
Discover how JAX-powered neural networks (NDNN) outperform PINNs in solving PDEs and shock wave problems with simple, accurate results.
Why Gradient Descent Converges (and Sometimes Doesn’t) in Neural Networks
19 Sept 2025
Optimizing neural networks with gradient descent and domain decomposition for faster, scalable, and more accurate AI training.
Neural Networks vs. Scalar Shock Waves
19 Sept 2025
AI-driven solver uses non-diffusive neural networks to tackle 1D hyperbolic conservation laws and shockwave interactions.
Neural Network Tools for Shock Wave Decomposition
19 Sept 2025
AI-powered neural networks simulate shock wave generation, interaction, and decomposition with faster, non-diffusive methods.
Can Neural Networks Capture Shock Waves Without Diffusion? This Paper Says Yes
19 Sept 2025
New NDNN method shows how neural networks can model entropic shock waves in HCLs without artificial diffusion or viscosity.
A Radical Neural Network Approach to Modeling Shock Dynamics
19 Sept 2025
New NDNN algorithm solves hyperbolic conservation laws with sharper shock tracking than PINNs, improving accuracy in PDE solutions.