Shock Wave

Shock waves, abrupt changes in pressure and density, are studied across diverse fields to understand their formation, propagation, and impact. Current research focuses on developing accurate and efficient computational models, employing techniques like physics-informed neural networks, relaxation neural networks, and deep learning-enhanced numerical schemes (e.g., WENO) to capture shock wave behavior in complex systems. These advancements are crucial for improving predictions in areas such as space weather forecasting (solar energetic particle events), traffic flow optimization, and simulations of supersonic flows and cosmological structure formation. The improved accuracy and efficiency of these models have significant implications for various scientific disciplines and engineering applications.