Application of machine learning methods on dynamic strength analysis for additive manufactured polypropylene-based composites

Application of machine learning methods on dynamic strength analysis for additive manufactured polypropylene-based composites

This study aimed at applying machine learning (ML) methods to analyze dynamic strength of 3D-printed polypropylene (PP)-based composites. The dynamic strength of additive manufactured PP-based composites with different fillers and printing parameters was investigated by split Hopkinson pressure bars...

Full description

Bibliographic Details
Main Authors: Ahzi, S. (Author), Baniassadi, M. (Author), Cai, R. (Author), Peng, Y. (Author), Wang, K. (Author), Wen, W. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2022
Subjects:
3D printers
Additive manufacturing
Additives
Computational efficiency
Decision trees
Dynamic materials
Dynamic strength
Efficiency
Forecasting
Machine learning
Machine learning algorithms
Machine learning approaches
Machine learning methods
Neural networks
ON dynamics
Performance
Polypropylene based composites
Polypropylene-based composites
Polypropylenes
Prediction
Split Hopkinson pressure bars
Strength analysis
Online Access:View Fulltext in Publisher

Internet

View Fulltext in Publisher

Similar Items