Energy-Based Error Bound of Physics-Informed Neural Network Solutions in Elasticity

An energy-based a posteriori error bound is proposed for the physics-informed neural network solutions of elasticity problems. admissible displacement-stress solution pair obtained from mixed form networks, and formulated as constitutive relation defined by pair. Such an estimator provides upper global discretization. The bounding property, well asymptotic behavior solutions, are studied in demonstration example.