All Stories

  1. A variational computational-based framework for unsteady incompressible flows
  2. Minimizing nature's cost: Exploring data-free physics-informed neural network solvers for fluid mechanics applications
  3. Physics-Informed Neural Networks: Leveraging the Principle of Minimum Pressure Gradient for Unsteady Fluid Dynamics
  4. On Predicting Magnus Force With Gauss-Constrained PINNs
  5. Enhancing lift and reducing wingtip vortices using a passive rotor on finite-span wings
  6. A Novel Approach for Data-Free, Physics-Informed Neural Networks in Fluid Mechanics Using the Principle of Minimum Pressure Gradient
  7. The Integration of Remotely Operated Vehicles ROVS and Autonomous Underwater Vehicles AUVS Using Subsea Wireless Communication
  8. Experimental investigation of the effect of prismatic roughness on the performance of belt skimmers in oil spill recovery applications