Physics-informed neural networks (PINNs) for inverse analysis: An illustration
This paper investigates the application of physics-informed neural networks (PINNs) to solve inverse problems in solid mechanics. Traditional numerical methods, such as finite element method (FEM) and isogeometric analysis (IGA), often require significant computational time, hindering their applicability in scenarios r...