Fig. 7From: Geometry aware physics informed neural network surrogate for solving Navier–Stokes equation (GAPINN)Comparison of loss over epoch during the network training for both vanilla PINN and the proposed GAPINN using hard and soft constraints for generating surrogate models for solving Navier–Stokes equations on non-parameterized geometries without the use of training data. Depicted is the error after each epochBack to article page