Christopher J. McDevitt

Regional accuracy of physics-informed neural networks (PINNs) for recirculation in a deep lid-driven cavity

Deep lid-driven cavities contain strong motion beneath the lid and much weaker recirculation at depth, so agreement in bulk velocity is an incomplete assessment of a computed flow. We examine data-free physics-informed neural networks (PINNs) for steady, two-dimensional incompressible flow in a cavity of depth-to-width...