Revealing the hot deformation behavior of AZ42 Mg alloy by using 3D hot processing map based on a novel NGO-ANN model
The hot deformation behavior of AZ42 alloy was observed using thermal compression tests at a temperature scope of 250–400 °C and strain rate scope of 0.001–1 s−1. True stress-strain curves exhibited a combination of work hardening and dynamic softening features. A Northern Goshawk algorithm (NGO)-op...
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ftdoajarticles:oai:doaj.org/article:1753bb929ab649dfae31f103e23c7ea8 2024-09-15T18:25:45+00:00 Revealing the hot deformation behavior of AZ42 Mg alloy by using 3D hot processing map based on a novel NGO-ANN model Mengtao Ning Xiaomin Chen Yongcheng Lin Hongwei Hu Xiaojie Zhou Jian Zhang Xianzheng Lu You Wu Jian Chen Qiang Shen 2023-11-01T00:00:00Z https://doi.org/10.1016/j.jmrt.2023.10.073 https://doaj.org/article/1753bb929ab649dfae31f103e23c7ea8 EN eng Elsevier http://www.sciencedirect.com/science/article/pii/S223878542302522X https://doaj.org/toc/2238-7854 2238-7854 doi:10.1016/j.jmrt.2023.10.073 https://doaj.org/article/1753bb929ab649dfae31f103e23c7ea8 Journal of Materials Research and Technology, Vol 27, Iss , Pp 2292-2310 (2023) AZ42 alloy Northern Goshawk optimization Artificial neural network model Processing map Mining engineering. Metallurgy TN1-997 article 2023 ftdoajarticles https://doi.org/10.1016/j.jmrt.2023.10.073 2024-08-05T17:49:59Z The hot deformation behavior of AZ42 alloy was observed using thermal compression tests at a temperature scope of 250–400 °C and strain rate scope of 0.001–1 s−1. True stress-strain curves exhibited a combination of work hardening and dynamic softening features. A Northern Goshawk algorithm (NGO)-optimized artificial neural network (ANN) model was proposed. The established NGO-ANN model demonstrated impressive prediction accuracy, achieving a high determination coefficient of 0.991, a mean absolute percentage error of 3.51 %, and a root mean square error of 2.73. Subsequently, three-dimensional (3D) hot processing map based on the dynamic material model (DMM) theory was created. There were three different regions within the processing maps: the flow instability region (region A: 250–260 °C, 0.02–1 s−1, and region B: 300–400 °C, 0.01–0.1 s−1), high-power dissipation coefficient region (region C: 350–400 °C, 0.001–0.02 s−1, and region D: 300–350 °C, 0.5–1 s−1), and low power dissipation efficiency safety region (region E: the rest ones). Microstructural analysis revealed significant local plastic flow features in the flow instability region and a combination of coarse initial deformation grains and fine dynamic recrystallization (DRX) grains in the low power dissipation efficiency safety region. Fine and uniform grains were observed in the high-power dissipation efficiency region with DRX degree VDRX as high as 85.6 %, resulting in the best mechanical properties. Based on the established 3D hot processing map, the optimal process domains were determined. Article in Journal/Newspaper Northern Goshawk Directory of Open Access Journals: DOAJ Articles Journal of Materials Research and Technology 27 2292 2310 |
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ftdoajarticles |
language |
English |
topic |
AZ42 alloy Northern Goshawk optimization Artificial neural network model Processing map Mining engineering. Metallurgy TN1-997 |
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AZ42 alloy Northern Goshawk optimization Artificial neural network model Processing map Mining engineering. Metallurgy TN1-997 Mengtao Ning Xiaomin Chen Yongcheng Lin Hongwei Hu Xiaojie Zhou Jian Zhang Xianzheng Lu You Wu Jian Chen Qiang Shen Revealing the hot deformation behavior of AZ42 Mg alloy by using 3D hot processing map based on a novel NGO-ANN model |
topic_facet |
AZ42 alloy Northern Goshawk optimization Artificial neural network model Processing map Mining engineering. Metallurgy TN1-997 |
description |
The hot deformation behavior of AZ42 alloy was observed using thermal compression tests at a temperature scope of 250–400 °C and strain rate scope of 0.001–1 s−1. True stress-strain curves exhibited a combination of work hardening and dynamic softening features. A Northern Goshawk algorithm (NGO)-optimized artificial neural network (ANN) model was proposed. The established NGO-ANN model demonstrated impressive prediction accuracy, achieving a high determination coefficient of 0.991, a mean absolute percentage error of 3.51 %, and a root mean square error of 2.73. Subsequently, three-dimensional (3D) hot processing map based on the dynamic material model (DMM) theory was created. There were three different regions within the processing maps: the flow instability region (region A: 250–260 °C, 0.02–1 s−1, and region B: 300–400 °C, 0.01–0.1 s−1), high-power dissipation coefficient region (region C: 350–400 °C, 0.001–0.02 s−1, and region D: 300–350 °C, 0.5–1 s−1), and low power dissipation efficiency safety region (region E: the rest ones). Microstructural analysis revealed significant local plastic flow features in the flow instability region and a combination of coarse initial deformation grains and fine dynamic recrystallization (DRX) grains in the low power dissipation efficiency safety region. Fine and uniform grains were observed in the high-power dissipation efficiency region with DRX degree VDRX as high as 85.6 %, resulting in the best mechanical properties. Based on the established 3D hot processing map, the optimal process domains were determined. |
format |
Article in Journal/Newspaper |
author |
Mengtao Ning Xiaomin Chen Yongcheng Lin Hongwei Hu Xiaojie Zhou Jian Zhang Xianzheng Lu You Wu Jian Chen Qiang Shen |
author_facet |
Mengtao Ning Xiaomin Chen Yongcheng Lin Hongwei Hu Xiaojie Zhou Jian Zhang Xianzheng Lu You Wu Jian Chen Qiang Shen |
author_sort |
Mengtao Ning |
title |
Revealing the hot deformation behavior of AZ42 Mg alloy by using 3D hot processing map based on a novel NGO-ANN model |
title_short |
Revealing the hot deformation behavior of AZ42 Mg alloy by using 3D hot processing map based on a novel NGO-ANN model |
title_full |
Revealing the hot deformation behavior of AZ42 Mg alloy by using 3D hot processing map based on a novel NGO-ANN model |
title_fullStr |
Revealing the hot deformation behavior of AZ42 Mg alloy by using 3D hot processing map based on a novel NGO-ANN model |
title_full_unstemmed |
Revealing the hot deformation behavior of AZ42 Mg alloy by using 3D hot processing map based on a novel NGO-ANN model |
title_sort |
revealing the hot deformation behavior of az42 mg alloy by using 3d hot processing map based on a novel ngo-ann model |
publisher |
Elsevier |
publishDate |
2023 |
url |
https://doi.org/10.1016/j.jmrt.2023.10.073 https://doaj.org/article/1753bb929ab649dfae31f103e23c7ea8 |
genre |
Northern Goshawk |
genre_facet |
Northern Goshawk |
op_source |
Journal of Materials Research and Technology, Vol 27, Iss , Pp 2292-2310 (2023) |
op_relation |
http://www.sciencedirect.com/science/article/pii/S223878542302522X https://doaj.org/toc/2238-7854 2238-7854 doi:10.1016/j.jmrt.2023.10.073 https://doaj.org/article/1753bb929ab649dfae31f103e23c7ea8 |
op_doi |
https://doi.org/10.1016/j.jmrt.2023.10.073 |
container_title |
Journal of Materials Research and Technology |
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27 |
container_start_page |
2292 |
op_container_end_page |
2310 |
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1810466229168635904 |