On the Zener–Hollomon Parameter, Multi-Layer Perceptron and Multivariate Polynomials in the Struggle for the Peak and Steady-State Description
Description of flow stress evolution, specifically an approximation of a set of flow curves acquired under a wide range of thermomechanical conditions, of various materials is often solved via so-called flow stress models. Some of these models are associated with a description of significant flow-cu...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | Metals |
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| Online Access: | https://www.mdpi.com/2075-4701/10/11/1413 |
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| author | Petr Opěla Petr Kawulok Ivo Schindler Rostislav Kawulok Stanislav Rusz Horymír Navrátil |
| author_facet | Petr Opěla Petr Kawulok Ivo Schindler Rostislav Kawulok Stanislav Rusz Horymír Navrátil |
| author_sort | Petr Opěla |
| collection | DOAJ |
| description | Description of flow stress evolution, specifically an approximation of a set of flow curves acquired under a wide range of thermomechanical conditions, of various materials is often solved via so-called flow stress models. Some of these models are associated with a description of significant flow-curve coordinates. It is clear, the more accurate the coordinates description, the more accurate the assembled model. In the presented research, Zener–Hollomon-based relations, multi-layer perceptron networks and multivariate polynomials are employed to describe the peak and steady-state coordinates of an Invar 36 flow curve dataset. Comparison of the utilized methods in the case of the studied alloy has showed that the suitable description is given by the multivariate polynomials although the Zener–Hollomon and perceptron networks also offer valuable results. |
| first_indexed | 2024-03-10T15:22:45Z |
| format | Article |
| id | doaj.art-7dd631f1a340464f9d8269f280d0df69 |
| institution | Directory Open Access Journal |
| issn | 2075-4701 |
| language | English |
| last_indexed | 2024-03-10T15:22:45Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metals |
| spelling | doaj.art-7dd631f1a340464f9d8269f280d0df692023-11-20T18:22:19ZengMDPI AGMetals2075-47012020-10-011011141310.3390/met10111413On the Zener–Hollomon Parameter, Multi-Layer Perceptron and Multivariate Polynomials in the Struggle for the Peak and Steady-State DescriptionPetr Opěla0Petr Kawulok1Ivo Schindler2Rostislav Kawulok3Stanislav Rusz4Horymír Navrátil5Faculty of Materials Science and Technology, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 70800 Ostrava-Poruba, Czech RepublicFaculty of Materials Science and Technology, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 70800 Ostrava-Poruba, Czech RepublicFaculty of Materials Science and Technology, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 70800 Ostrava-Poruba, Czech RepublicFaculty of Materials Science and Technology, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 70800 Ostrava-Poruba, Czech RepublicFaculty of Materials Science and Technology, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 70800 Ostrava-Poruba, Czech RepublicFaculty of Materials Science and Technology, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 70800 Ostrava-Poruba, Czech RepublicDescription of flow stress evolution, specifically an approximation of a set of flow curves acquired under a wide range of thermomechanical conditions, of various materials is often solved via so-called flow stress models. Some of these models are associated with a description of significant flow-curve coordinates. It is clear, the more accurate the coordinates description, the more accurate the assembled model. In the presented research, Zener–Hollomon-based relations, multi-layer perceptron networks and multivariate polynomials are employed to describe the peak and steady-state coordinates of an Invar 36 flow curve dataset. Comparison of the utilized methods in the case of the studied alloy has showed that the suitable description is given by the multivariate polynomials although the Zener–Hollomon and perceptron networks also offer valuable results.https://www.mdpi.com/2075-4701/10/11/1413flow stress descriptionpeak and steady-state descriptionregression analysisZener–Hollomon parameterartificial neural networksmultivariate polynomials |
| spellingShingle | Petr Opěla Petr Kawulok Ivo Schindler Rostislav Kawulok Stanislav Rusz Horymír Navrátil On the Zener–Hollomon Parameter, Multi-Layer Perceptron and Multivariate Polynomials in the Struggle for the Peak and Steady-State Description Metals flow stress description peak and steady-state description regression analysis Zener–Hollomon parameter artificial neural networks multivariate polynomials |
| title | On the Zener–Hollomon Parameter, Multi-Layer Perceptron and Multivariate Polynomials in the Struggle for the Peak and Steady-State Description |
| title_full | On the Zener–Hollomon Parameter, Multi-Layer Perceptron and Multivariate Polynomials in the Struggle for the Peak and Steady-State Description |
| title_fullStr | On the Zener–Hollomon Parameter, Multi-Layer Perceptron and Multivariate Polynomials in the Struggle for the Peak and Steady-State Description |
| title_full_unstemmed | On the Zener–Hollomon Parameter, Multi-Layer Perceptron and Multivariate Polynomials in the Struggle for the Peak and Steady-State Description |
| title_short | On the Zener–Hollomon Parameter, Multi-Layer Perceptron and Multivariate Polynomials in the Struggle for the Peak and Steady-State Description |
| title_sort | on the zener hollomon parameter multi layer perceptron and multivariate polynomials in the struggle for the peak and steady state description |
| topic | flow stress description peak and steady-state description regression analysis Zener–Hollomon parameter artificial neural networks multivariate polynomials |
| url | https://www.mdpi.com/2075-4701/10/11/1413 |
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