Hybrid Mechanistic Neural Network Modelling of the Degree of Cure of Polymer Composite

Samuel Sells, Jie Zhang

2024

Abstract

A hybrid mechanistic/neural network model was developed for the industrial polymer composite curing process of a fibre-reinforced polymer composite. A hybrid model with parallel scheme and a hybrid model with the combination of series and parallel schemes were developed. It is found that the hybrid model with the combination of series and parallel schemes gives better performance. It is shown that the developed hybrid model is more accurate than its mechanistic and neural network counterparts in predicting the degree of cure based upon the temperature and time data. The hybrid model is 7.7% and 17.1% more accurate than the neural network model and the mechanistic model respectively in terms of sum of absolute errors.

Paper Citation

in Harvard Style

Sells S. and Zhang J. (2024). Hybrid Mechanistic Neural Network Modelling of the Degree of Cure of Polymer Composite. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-680-4, SciTePress, pages 614-621. DOI: 10.5220/0012469300003636

in Bibtex Style

@conference{icaart24,
author={Samuel Sells and Jie Zhang},
title={Hybrid Mechanistic Neural Network Modelling of the Degree of Cure of Polymer Composite},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2024},
pages={614-621},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012469300003636},
isbn={978-989-758-680-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Hybrid Mechanistic Neural Network Modelling of the Degree of Cure of Polymer Composite
SN - 978-989-758-680-4
AU - Sells S.
AU - Zhang J.
PY - 2024
SP - 614
EP - 621
DO - 10.5220/0012469300003636
PB - SciTePress