FEM-ANN approach to predict nonlinear pyro-coupled deflection of sandwich plates with agglomerated porous nanocomposite core and piezo-magneto-elastic facings in thermal environment

The present work deals with evaluating the nonlinear deflections of smart sandwich plate agglomerated Carbon Nanotubes (CNTs) porous core and piezo-magneto-electric (PME) facings, using a novel finite element method (FEM) – artificial neural network (ANN) approach. For first time, an ANN-based computational tool that integrates effects agglomeration CNTs, porosity pyro-coupling PME materials is presented. Firstly, in-house (FE) proposed developed principle virtual in association higher-order shear deformation theory (HSDT) von-Karman’s nonlinearity. data points owing to are collected FE formulation, which trains ANN model Levenberg–Marquardt algorithm. externally applied thermal loads assumed vary uniformly linearly across thickness plate. primary focus this assess variation degree associated porosity. Two states agglomeration, such as partial complete; three forms porosity, distributed, two variants functionally graded considered for investigation. Numerical examples solved understand interrelated these material properties. A significant deflection plate, refers its actuation capability, witnessed when parameters change.