City Research Online

Abstract

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

Publication Type:	Article
Additional Information:	Copyright 2023 The Author(s). Published with license by Taylor & Francis Group, LLCThis is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon inany way.
Publisher Keywords:	Artificial neural network (ANN), agglomeration, porosity, pyro-coupling, piezo-magneto, deflection, finite element
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) T Technology > TS Manufactures
Departments:	School of Science & Technology > Engineering
SWORD Depositor:	Symplectic Administrator

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