Neural Network-Based Prediction Model to Investigate the Influence of Temperature and Moisture on Vibration Characteristics of Skew Laminated Composite Sandwich Plates

Neural Network-Based Prediction Model to Investigate the Influence of Temperature and Moisture on Vibration Characteristics of Skew Laminated Composite Sandwich Plates

The present study deals with the development of a prediction model to investigate the impact of temperature and moisture on the vibration response of a skew laminated composite sandwich (LCS) plate using the artificial neural network (ANN) technique. Firstly, a finite element model is generated to i...

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Bibliographic Details
Main Authors: Vinayak Kallannavar, Subhaschandra Kattimani, Manzoore Elahi M. Soudagar, M. A. Mujtaba, Saad Alshahrani, Muhammad Imran
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Materials
Subjects:
artificial neural network
finite element analysis
shear deformation theory
skew angle
sandwich plates
effect of temperature and moisture
Online Access:https://www.mdpi.com/1996-1944/14/12/3170

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