An accurate coarse mesh-based analysis approach for nonlinear bending and post-buckling problems of plates and shells utilizing recurrent neural networks with Bayesian regularization back-propagation algorithm

The fineness of element meshes strongly affects the accuracy and cost of solutions in computational mechanics. In this regards, an accurate coarse mesh-based analysis approach (CMA) for nonlinear bending and post-buckling problems of plates and shells utilizing nonlinear auto-regressive exogenous Bayesian neural networks (NARX-BNNs) is first proposed in this work. The CMA approach comprises two pivotal stages. Initially, a coarse mesh-based post-buckling isogeometric analysis is executed, yieldi