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Volume 15
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10.3390/ma15030721
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Article

Application of an Artificial Neural Network in the Modelling of Heat Curing Effects on the Strength of Adhesive Joints at Elevated Temperature with Imprecise Adhesive Mix Ratios

by
Jakub Szabelski
1,*,
Robert Karpiński
2,* and
Anna Machrowska
2
1
Department of Computerization and Production Robotization, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland
2
Department of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland
*
Authors to whom correspondence should be addressed.
Materials 2022, 15(3), 721; https://doi.org/10.3390/ma15030721
Submission received: 18 November 2021 / Revised: 14 January 2022 / Accepted: 16 January 2022 / Published: 18 January 2022
(This article belongs to the Special Issue Computer-Aided Design and Modeling of Materials at Different Scales)
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Abstract

This paper is a discussion of the results of tests intended to (i) estimate the effects of component mix ratios and heat curing of an adhesive joint on the tensile strength, and (ii) to determine the adhesive component mix ratio for which heat curing is insignificant to the strength of adhesive butt joints. Experimental tests were carried out at ambient temperature and elevated temperature during which adhesive butt joints were loaded with a tensile force until failure. The variables were the mix ratio of epoxy adhesive components and the application of heat holding at the adhesive curing stage. An LSTM (long short-time memory) forecast was used to determine the point corresponding to the mix ratio of adhesive components at which heat holding of the adhesive joint no longer has a positive and significant importance to the final tensile strength of the joint.
Keywords: artificial neural networks; LSTM; modelling; adhesive joints; epoxy; resin; hardener; mix ratio; temperature degradation artificial neural networks; LSTM; modelling; adhesive joints; epoxy; resin; hardener; mix ratio; temperature degradation

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MDPI and ACS Style

Szabelski, J.; Karpiński, R.; Machrowska, A. Application of an Artificial Neural Network in the Modelling of Heat Curing Effects on the Strength of Adhesive Joints at Elevated Temperature with Imprecise Adhesive Mix Ratios. Materials 2022, 15, 721. https://doi.org/10.3390/ma15030721

AMA Style

Szabelski J, Karpiński R, Machrowska A. Application of an Artificial Neural Network in the Modelling of Heat Curing Effects on the Strength of Adhesive Joints at Elevated Temperature with Imprecise Adhesive Mix Ratios. Materials. 2022; 15(3):721. https://doi.org/10.3390/ma15030721

Chicago/Turabian Style

Szabelski, Jakub, Robert Karpiński, and Anna Machrowska. 2022. "Application of an Artificial Neural Network in the Modelling of Heat Curing Effects on the Strength of Adhesive Joints at Elevated Temperature with Imprecise Adhesive Mix Ratios" Materials 15, no. 3: 721. https://doi.org/10.3390/ma15030721

APA Style

Szabelski, J., Karpiński, R., & Machrowska, A. (2022). Application of an Artificial Neural Network in the Modelling of Heat Curing Effects on the Strength of Adhesive Joints at Elevated Temperature with Imprecise Adhesive Mix Ratios. Materials, 15(3), 721. https://doi.org/10.3390/ma15030721

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