Physics-informed hybrid learning for bending analysis of multidirectional porous FG shells
A thorough Physics-Informed Machine Learning framework that integrates an improved higher-order shear deformation theory with a finite element formulation to forecast the bending behavior of multidirectional functionally graded (MFG) porous metal foam doubly curved shells is created.