Parametric and inverse analysis of flow inside an obstructed channel under the influence of magnetic field using physics informed neural networks

Documenti analoghi

• Evaluating Joule heating influence on heat transfer and entropy generation in MHD channel flow: A parametric study and ill-posed problem solution using PINNs
  di: Ghaderi, Ehsan, et al.
  Pubblicazione: (2024)
• Intelligent Optimization of Multi-Parameter Micromixers Using a Scientific Machine Learning Framework
  di: Hassanzadeh, Meraj, et al.
  Pubblicazione: (2025)
• On the Non-Markovian Navier-Stokes Framework for Turbulence Modeling -- A Preliminary Analysis
  di: Hannani, Siamak Kazemzadeh, et al.
  Pubblicazione: (2025)
• Equation Discovery, Parametric Simulation, and Optimization Using the Physics-Informed Neural Network (PINN) Method for the Heat Conduction Problem
  di: Ghaderi, Ehsan, et al.
  Pubblicazione: (2025)
• FlexPINN: Modeling Fluid Dynamics and Mass Transfer in 3D Micromixer Geometries Using a Flexible Physics-Informed Neural Network
  di: Hassanzadeh, Meraj, et al.
  Pubblicazione: (2025)