2 papers
physics.flu-dyn2026
A Physics-Informed Spatiotemporal Deep Learning Framework for Turbulent Systems
Luca Menicali, Andrew Grace, David H. Richter +1
Fluid thermodynamics underpins atmospheric dynamics, climate science, industrial applications, and energy systems. However, direct numerical simulations (DNS) of such systems can b…
physics.flu-dyn2025
Physics-Informed Priors with Application to Boundary Layer Velocity
Luca Menicali, David H. Richter, Stefano Castruccio
One of the most popular recent areas of machine learning predicates the use of neural networks augmented by information about the underlying process in the form of Partial Differen…