Application of Neural Network Models with Ultra-Small Samples to Optimize the Ultrasonic Consolidation Parameters for ‘PEI Adherend/Prepreg (CF-PEI Fabric)/PEI Adherend’ Lap Joints

Application of Neural Network Models with Ultra-Small Samples to Optimize the Ultrasonic Consolidation Parameters for ‘PEI Adherend/Prepreg (CF-PEI Fabric)/PEI Adherend’ Lap Joints

The aim of this study was to optimize the ultrasonic consolidation (USC) parameters for ‘PEI adherend/Prepreg (CF-PEI fabric)/PEI adherend’ lap joints. For this purpose, artificial neural network (ANN) simulation was carried out. Two ANNs were trained using an ultra-small data sample, which did not...

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Bibliographic Details
Main Authors: Dmitry Y. Stepanov, Defang Tian, Vladislav O. Alexenko, Sergey V. Panin, Dmitry G. Buslovich
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Polymers
Subjects:
machine learning
neural network simulation
carbon fiber fabric
ultrasonic consolidation
lap joint
PEI
Online Access:https://www.mdpi.com/2073-4360/16/4/451

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