Physical and Numerical Simulations for Predicting Distribution of Microstructural Features during Thermomechanical Processing of Steels
The design of modern construction materials with heterogeneous microstructures requires a numerical model that can predict the distribution of microstructural features instead of average values. The accuracy and reliability of such models depend on the proper identification of the coefficients for a...
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2022-02-01
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| author | Łukasz Poloczek Roman Kuziak Valeriy Pidvysots’kyy Danuta Szeliga Jan Kusiak Maciej Pietrzyk |
| author_facet | Łukasz Poloczek Roman Kuziak Valeriy Pidvysots’kyy Danuta Szeliga Jan Kusiak Maciej Pietrzyk |
| author_sort | Łukasz Poloczek |
| collection | DOAJ |
| description | The design of modern construction materials with heterogeneous microstructures requires a numerical model that can predict the distribution of microstructural features instead of average values. The accuracy and reliability of such models depend on the proper identification of the coefficients for a particular material. This work was motivated by the need for advanced experimental data to identify stochastic material models. Extensive experiments were performed to supply data to identify a model of austenite microstructure evolution in steels during hot deformation and during the interpass times between deformations. Two sets of tests were performed. The first set involved hot compressions with a nominal strain of 1. The second set involved hot compressions with lower nominal strains, followed by holding at the deformation temperature for different times. Histograms of austenite grain size after each test were measured and used in the identification procedure. The stochastic model, which was developed elsewhere, was identified. Inverse analysis with the objective function based on the distance between the measured and calculated histograms was applied. Validation of the model was performed for the experiments, which were not used in the identification. The distance between the measured and calculated histograms was determined for each test using the Bhattacharyya metric and very low values were obtained. As a case study, the model with the optimal coefficients was applied to the simulation of the selected industrial hot-forming process. |
| first_indexed | 2024-03-09T20:34:22Z |
| format | Article |
| id | doaj.art-bf44645c7bb2464d820cee48b209fd9c |
| institution | Directory Open Access Journal |
| issn | 1996-1944 |
| language | English |
| last_indexed | 2024-03-09T20:34:22Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
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| series | Materials |
| spelling | doaj.art-bf44645c7bb2464d820cee48b209fd9c2023-11-23T23:16:54ZengMDPI AGMaterials1996-19442022-02-01155166010.3390/ma15051660Physical and Numerical Simulations for Predicting Distribution of Microstructural Features during Thermomechanical Processing of SteelsŁukasz Poloczek0Roman Kuziak1Valeriy Pidvysots’kyy2Danuta Szeliga3Jan Kusiak4Maciej Pietrzyk5Łukasiewicz Research Network-Institute for Ferrous Metallurgy, ul. K. Miarki 12, 44-100 Gliwice, PolandŁukasiewicz Research Network-Institute for Ferrous Metallurgy, ul. K. Miarki 12, 44-100 Gliwice, PolandŁukasiewicz Research Network-Institute for Ferrous Metallurgy, ul. K. Miarki 12, 44-100 Gliwice, PolandDepartment of Applied Computer Science and Modeling, Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, PolandDepartment of Applied Computer Science and Modeling, Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, PolandDepartment of Applied Computer Science and Modeling, Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, PolandThe design of modern construction materials with heterogeneous microstructures requires a numerical model that can predict the distribution of microstructural features instead of average values. The accuracy and reliability of such models depend on the proper identification of the coefficients for a particular material. This work was motivated by the need for advanced experimental data to identify stochastic material models. Extensive experiments were performed to supply data to identify a model of austenite microstructure evolution in steels during hot deformation and during the interpass times between deformations. Two sets of tests were performed. The first set involved hot compressions with a nominal strain of 1. The second set involved hot compressions with lower nominal strains, followed by holding at the deformation temperature for different times. Histograms of austenite grain size after each test were measured and used in the identification procedure. The stochastic model, which was developed elsewhere, was identified. Inverse analysis with the objective function based on the distance between the measured and calculated histograms was applied. Validation of the model was performed for the experiments, which were not used in the identification. The distance between the measured and calculated histograms was determined for each test using the Bhattacharyya metric and very low values were obtained. As a case study, the model with the optimal coefficients was applied to the simulation of the selected industrial hot-forming process.https://www.mdpi.com/1996-1944/15/5/1660plastometric testsstress relaxation testsstochastic modelmicrostructure evolutioninverse analysisidentification |
| spellingShingle | Łukasz Poloczek Roman Kuziak Valeriy Pidvysots’kyy Danuta Szeliga Jan Kusiak Maciej Pietrzyk Physical and Numerical Simulations for Predicting Distribution of Microstructural Features during Thermomechanical Processing of Steels Materials plastometric tests stress relaxation tests stochastic model microstructure evolution inverse analysis identification |
| title | Physical and Numerical Simulations for Predicting Distribution of Microstructural Features during Thermomechanical Processing of Steels |
| title_full | Physical and Numerical Simulations for Predicting Distribution of Microstructural Features during Thermomechanical Processing of Steels |
| title_fullStr | Physical and Numerical Simulations for Predicting Distribution of Microstructural Features during Thermomechanical Processing of Steels |
| title_full_unstemmed | Physical and Numerical Simulations for Predicting Distribution of Microstructural Features during Thermomechanical Processing of Steels |
| title_short | Physical and Numerical Simulations for Predicting Distribution of Microstructural Features during Thermomechanical Processing of Steels |
| title_sort | physical and numerical simulations for predicting distribution of microstructural features during thermomechanical processing of steels |
| topic | plastometric tests stress relaxation tests stochastic model microstructure evolution inverse analysis identification |
| url | https://www.mdpi.com/1996-1944/15/5/1660 |
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