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Flexural wave propagation characteristics of advanced nanocomposites reinforced sandwich structure via 3D-flexibility-deep neural networks approaches.

Authors :
Yang, Xiaohua
Jiang, Lijian
Long, Feng
Abouel Nasr, Emad
Source :
Mechanics Based Design of Structures & Machines. 2024, Vol. 52 Issue 12, p10583-10611. 29p.
Publication Year :
2024

Abstract

The propagation of flexural waves in advanced nanocomposites reinforced sandwich structures is a topic of paramount importance in the field of structural engineering and materials science. This study investigates the dynamic behavior of such structures, focusing on the wave propagation characteristics along with longitude and lateral directions and their influence on structural performance. Advanced nanocomposites, with their unique material properties and enhanced mechanical properties, offer promising opportunities for the development of lightweight and high-strength sandwich structures. For this important aim, first, a mathematical modeling using three-dimensional flexibility theory and an analytical solution procedure, the results are collected. After that using the datasets of the mathematical modeling section, the hybrid deep neural networks are trained, tested, and validated. Through comprehensive analytical simulations and machine network validations, this research elucidates the complex interplay between material composition, structural geometry, and wave propagation phenomena. Key parameters, such as wave velocity, dispersion, and geometry conditions are analyzed to gain insights into the dynamic response of the sandwich structure. The findings contribute to a deeper understanding of the underlying physics governing flexural wave propagation in nanocomposite-reinforced sandwich structures, thereby facilitating the design and optimization of lightweight and resilient structural systems for diverse engineering applications. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15397734
Volume :
52
Issue :
12
Database :
Academic Search Index
Journal :
Mechanics Based Design of Structures & Machines
Publication Type :
Academic Journal
Accession number :
181055442
Full Text :
https://doi.org/10.1080/15397734.2024.2357261