Size-dependent nonlinear vibrations of functionally graded origami-enabled auxetic metamaterial plate: Application of artificial intelligence networks for solving the engineering problem
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{CHEN:2024:mtcomm,
-
author = "Fenghua Chen and Xinguo Qiu and Khalid A. Alnowibet",
-
title = "Size-dependent nonlinear vibrations of functionally
graded origami-enabled auxetic metamaterial plate:
Application of artificial intelligence networks for
solving the engineering problem",
-
journal = "Materials Today Communications",
-
volume = "38",
-
pages = "108232",
-
year = "2024",
-
ISSN = "2352-4928",
-
DOI = "doi:10.1016/j.mtcomm.2024.108232",
-
URL = "https://www.sciencedirect.com/science/article/pii/S2352492824002125",
-
keywords = "genetic algorithms, genetic programming, Nonlinear
behavior, Pseudo-arc-length continuation approach,
GOEAMs, Microplate, Artificial intelligence network",
-
abstract = "Auxetic metamaterials are a kind of advanced materials
that have distinct mechanical and physical
characteristics that are not seen in traditional
materials. This study presents a new concept for a
microplate composed of graphene origami (GOri)-enabled
auxetic metamaterials (GOEAMs) with functionally graded
(FG) properties. The research also examines the
nonlinear free vibration behavior of the microplate,
which is reinforced by the GOEAMs. The microplate is
composed of many layers of GOEAMs, with the GOri
content varying in a layer-wise manner across the
thickness. This variation in content allows for the
graded modification of the auxetic property and other
material characteristics. These modifications may be
accurately determined using micromechanical models
helped by genetic programming (GP). The modified couple
stress theory (MCST) is used to accurately represent
the microstructure of the current plate, given its
size. This theory incorporates a single-length scale
parameter. This study uses the first-order shear
deformation theory and includes von Karman type
nonlinearity to establish the nonlinear kinematic
equations. These equations are then solved numerically
using the generalized differential quadrature (GDQ)
method and pseudo-arc-length continuation approach. we
use mathematical modeling to collect data on the
nonlinear frequency and deflection of the FG microplate
made of GOEAMs. The data is then preprocessed by
normalizing the input features and splitting the
dataset into training and validation sets.
Subsequently, an artificial intelligence network (AIN)
architecture is constructed, consisting of an input
layer, hidden layers, and an output layer. Once the AIN
has been used to test, train, and validate the
findings, this approach may be used in future studies
on the nonlinear frequency and deflection of FG
microplates built of GOEAMs, with reduced computational
cost. Ultimately, the findings suggest that the
nonlinear free vibration characteristics of the
microplate may be successfully adjusted by manipulating
the GOri parameter and distribution",
- }
Genetic Programming entries for
Fenghua Chen
Xinguo Qiu
Khalid A Alnowibet
Citations