Predicting the strain hardening behavior and constructing processing maps of a lightweight Fe–Mn–Al–C steel through phenomenological modelling
This research deals with predicting the strain hardening behavior and constructing the processing maps of a lightweight steel over a wide range of temperature. To achieve this, the tensile tests were conducted at temperatures of 100 °C–1100 °C under strain rates of 0.001, 0.01, and 0.1s−1 up to frac...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-05-01
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| Series: | Journal of Materials Research and Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2238785424007750 |
| _version_ | 1797214907780825088 |
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| author | Iman Rahimi Hamid Reza Abedi |
| author_facet | Iman Rahimi Hamid Reza Abedi |
| author_sort | Iman Rahimi |
| collection | DOAJ |
| description | This research deals with predicting the strain hardening behavior and constructing the processing maps of a lightweight steel over a wide range of temperature. To achieve this, the tensile tests were conducted at temperatures of 100 °C–1100 °C under strain rates of 0.001, 0.01, and 0.1s−1 up to fracture. In order to predict the deformation behavior of the lightweight steel, strain compensated Arrhenius-type models were employed. Considering the wide temperature range under investigation, the activation energies and strain rate sensitivity coefficients substantially varied, therefore, three different temperature ranges of 25–200 °C, 300–600 °C, and 700–1000 °C were considered for the prediction of the flow stress level. To evaluate the accuracy of the applied models, the (i) root mean square error (RMSE), (ii) average absolute relative error (AARE), and (iii) correlation coefficient (R), were calculated as well-known statistical parameters. A good agreement was observed between the predicted and actual flow stress. Employing the predicted data, the strain hardening curves were plotted and power dissipation/instability maps were constructed at various strain levels and temperature ranges. The rapid hardening regions, the regions with high efficiency and instability regions were identified which would be valuable for industrialization of the experimented material. |
| first_indexed | 2024-04-24T11:21:38Z |
| format | Article |
| id | doaj.art-9a2971f8a88e4f1ea45e7ec7ef13c9ec |
| institution | Directory Open Access Journal |
| issn | 2238-7854 |
| language | English |
| last_indexed | 2024-04-24T11:21:38Z |
| publishDate | 2024-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Materials Research and Technology |
| spelling | doaj.art-9a2971f8a88e4f1ea45e7ec7ef13c9ec2024-04-11T04:41:20ZengElsevierJournal of Materials Research and Technology2238-78542024-05-013028912901Predicting the strain hardening behavior and constructing processing maps of a lightweight Fe–Mn–Al–C steel through phenomenological modellingIman Rahimi0Hamid Reza Abedi1School of Metallurgy & Materials Engineering, Iran University of Science and Technology (IUST), Tehran, IranCorresponding author.; School of Metallurgy & Materials Engineering, Iran University of Science and Technology (IUST), Tehran, IranThis research deals with predicting the strain hardening behavior and constructing the processing maps of a lightweight steel over a wide range of temperature. To achieve this, the tensile tests were conducted at temperatures of 100 °C–1100 °C under strain rates of 0.001, 0.01, and 0.1s−1 up to fracture. In order to predict the deformation behavior of the lightweight steel, strain compensated Arrhenius-type models were employed. Considering the wide temperature range under investigation, the activation energies and strain rate sensitivity coefficients substantially varied, therefore, three different temperature ranges of 25–200 °C, 300–600 °C, and 700–1000 °C were considered for the prediction of the flow stress level. To evaluate the accuracy of the applied models, the (i) root mean square error (RMSE), (ii) average absolute relative error (AARE), and (iii) correlation coefficient (R), were calculated as well-known statistical parameters. A good agreement was observed between the predicted and actual flow stress. Employing the predicted data, the strain hardening curves were plotted and power dissipation/instability maps were constructed at various strain levels and temperature ranges. The rapid hardening regions, the regions with high efficiency and instability regions were identified which would be valuable for industrialization of the experimented material.http://www.sciencedirect.com/science/article/pii/S2238785424007750Lightweight steelArrhenius modelProcessing mapStrain hardeningThermomechanical processing |
| spellingShingle | Iman Rahimi Hamid Reza Abedi Predicting the strain hardening behavior and constructing processing maps of a lightweight Fe–Mn–Al–C steel through phenomenological modelling Journal of Materials Research and Technology Lightweight steel Arrhenius model Processing map Strain hardening Thermomechanical processing |
| title | Predicting the strain hardening behavior and constructing processing maps of a lightweight Fe–Mn–Al–C steel through phenomenological modelling |
| title_full | Predicting the strain hardening behavior and constructing processing maps of a lightweight Fe–Mn–Al–C steel through phenomenological modelling |
| title_fullStr | Predicting the strain hardening behavior and constructing processing maps of a lightweight Fe–Mn–Al–C steel through phenomenological modelling |
| title_full_unstemmed | Predicting the strain hardening behavior and constructing processing maps of a lightweight Fe–Mn–Al–C steel through phenomenological modelling |
| title_short | Predicting the strain hardening behavior and constructing processing maps of a lightweight Fe–Mn–Al–C steel through phenomenological modelling |
| title_sort | predicting the strain hardening behavior and constructing processing maps of a lightweight fe mn al c steel through phenomenological modelling |
| topic | Lightweight steel Arrhenius model Processing map Strain hardening Thermomechanical processing |
| url | http://www.sciencedirect.com/science/article/pii/S2238785424007750 |
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