Litcius/Paper detail

Reconstructing turbulent velocity and pressure fields from under-resolved noisy particle tracks using physics-informed neural networks

Patricio Clark Di Leoni, Karuna Agarwal, Tamer A. Zaki, Charles Meneveau, Joseph Katz

2023Experiments in Fluids57 citationsDOI

Topics & Concepts

Particle velocityTurbulencePhysicsEulerian pathArtificial neural networkReynolds numberParticle (ecology)Statistical physicsMechanicsField (mathematics)Classical mechanicsComputational physicsComputer scienceMathematicsArtificial intelligenceTheoretical physicsLagrangianOceanographyGeologyPure mathematicsModel Reduction and Neural NetworksFluid Dynamics and Turbulent FlowsAerodynamics and Acoustics in Jet Flows
Reconstructing turbulent velocity and pressure fields from under-resolved noisy particle tracks using physics-informed neural networks | Litcius