Version 1
: Received: 18 March 2024 / Approved: 18 March 2024 / Online: 19 March 2024 (14:40:03 CET)
How to cite:
Goričan, T.; Terčelj, M.; Peruš, I. Automatic Explanation Of Metal’s Phenomena By Application Of Artificial Neural Networks – Use Case For Hot Extruded Aluminum Alloy 6082. Preprints2024, 2024031074. https://doi.org/10.20944/preprints202403.1074.v1
Goričan, T.; Terčelj, M.; Peruš, I. Automatic Explanation Of Metal’s Phenomena By Application Of Artificial Neural Networks – Use Case For Hot Extruded Aluminum Alloy 6082. Preprints 2024, 2024031074. https://doi.org/10.20944/preprints202403.1074.v1
Goričan, T.; Terčelj, M.; Peruš, I. Automatic Explanation Of Metal’s Phenomena By Application Of Artificial Neural Networks – Use Case For Hot Extruded Aluminum Alloy 6082. Preprints2024, 2024031074. https://doi.org/10.20944/preprints202403.1074.v1
APA Style
Goričan, T., Terčelj, M., & Peruš, I. (2024). Automatic Explanation Of Metal’s Phenomena By Application Of Artificial Neural Networks – Use Case For Hot Extruded Aluminum Alloy 6082. Preprints. https://doi.org/10.20944/preprints202403.1074.v1
Chicago/Turabian Style
Goričan, T., Milan Terčelj and Iztok Peruš. 2024 "Automatic Explanation Of Metal’s Phenomena By Application Of Artificial Neural Networks – Use Case For Hot Extruded Aluminum Alloy 6082" Preprints. https://doi.org/10.20944/preprints202403.1074.v1
Abstract
Artificial intelligence methods, especially artificial neural networks (ANNs), have recently been successfully used more and more frequently in the mathematical description of physical phenomena in the processing of metallic materials. Results based on measured data of phenomena in real production are often, at least locally, different or more complex than the results of established theories. In general, ANN models, which mostly work as "black boxes", allow us to improve production efficiency by themselves. The fact is, however, that a better understanding of the phenomena under consideration, which is otherwise enabled by classical mathematical approaches in the form of explicit mathematical formulas, could ensure even greater efficiency. In this article, therefore, a general concept is proposed to explain the discussed phenomena in metallic materials. The application of the concept is illustrated on the example of hot extrusion of aluminum alloy 6082, where CAE is used as an artificial neural network to model the phenomenon and predict the key parameters of the phenomenon. ChatGPT is used to explain the results according to the proposed concept. The basic idea is to enable practicing engineers to better understand the considered phenomena and results obtained by ANNs.
Keywords
Artificial Neural Networks; Automatic Explanation; Hot Extrusion; Aluminum Alloy; large language models; ChatGPT
Subject
Chemistry and Materials Science, Materials Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
