Application of Metamodels to Identification of Metallic Materials Models
Improvement of the efficiency of the inverse analysis (IA) for various material tests was the objective of the paper. Flow stress models and microstructure evolution models of various complexity of mathematical formulation were considered. Different types of experiments were performed and the result...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-01-01
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| Series: | Advances in Materials Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2016/2357534 |
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| author | Maciej Pietrzyk Jan Kusiak Danuta Szeliga Łukasz Rauch Łukasz Sztangret Grzegorz Górecki |
| author_facet | Maciej Pietrzyk Jan Kusiak Danuta Szeliga Łukasz Rauch Łukasz Sztangret Grzegorz Górecki |
| author_sort | Maciej Pietrzyk |
| collection | DOAJ |
| description | Improvement of the efficiency of the inverse analysis (IA) for various material tests was the objective of the paper. Flow stress models and microstructure evolution models of various complexity of mathematical formulation were considered. Different types of experiments were performed and the results were used for the identification of models. Sensitivity analysis was performed for all the models and the importance of parameters in these models was evaluated. Metamodels based on artificial neural network were proposed to simulate experiments in the inverse solution. Performed analysis has shown that significant decrease of the computing times could be achieved when metamodels substitute finite element model in the inverse analysis, which is the case in the identification of flow stress models. Application of metamodels gave good results for flow stress models based on closed form equations accounting for an influence of temperature, strain, and strain rate (4 coefficients) and additionally for softening due to recrystallization (5 coefficients) and for softening and saturation (7 coefficients). Good accuracy and high efficiency of the IA were confirmed. On the contrary, identification of microstructure evolution models, including phase transformation models, did not give noticeable reduction of the computing time. |
| format | Article |
| id | doaj-art-b294b303e5b1446ca2bd6f6d37207d1f |
| institution | Kabale University |
| issn | 1687-8434 1687-8442 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Materials Science and Engineering |
| spelling | doaj-art-b294b303e5b1446ca2bd6f6d37207d1f2025-08-20T03:39:21ZengWileyAdvances in Materials Science and Engineering1687-84341687-84422016-01-01201610.1155/2016/23575342357534Application of Metamodels to Identification of Metallic Materials ModelsMaciej Pietrzyk0Jan Kusiak1Danuta Szeliga2Łukasz Rauch3Łukasz Sztangret4Grzegorz Górecki5AGH University of Science and Technology, Aleja Adama Mickiewicza 30, 30-059 Kraków, PolandAGH University of Science and Technology, Aleja Adama Mickiewicza 30, 30-059 Kraków, PolandAGH University of Science and Technology, Aleja Adama Mickiewicza 30, 30-059 Kraków, PolandAGH University of Science and Technology, Aleja Adama Mickiewicza 30, 30-059 Kraków, PolandAGH University of Science and Technology, Aleja Adama Mickiewicza 30, 30-059 Kraków, PolandAGH University of Science and Technology, Aleja Adama Mickiewicza 30, 30-059 Kraków, PolandImprovement of the efficiency of the inverse analysis (IA) for various material tests was the objective of the paper. Flow stress models and microstructure evolution models of various complexity of mathematical formulation were considered. Different types of experiments were performed and the results were used for the identification of models. Sensitivity analysis was performed for all the models and the importance of parameters in these models was evaluated. Metamodels based on artificial neural network were proposed to simulate experiments in the inverse solution. Performed analysis has shown that significant decrease of the computing times could be achieved when metamodels substitute finite element model in the inverse analysis, which is the case in the identification of flow stress models. Application of metamodels gave good results for flow stress models based on closed form equations accounting for an influence of temperature, strain, and strain rate (4 coefficients) and additionally for softening due to recrystallization (5 coefficients) and for softening and saturation (7 coefficients). Good accuracy and high efficiency of the IA were confirmed. On the contrary, identification of microstructure evolution models, including phase transformation models, did not give noticeable reduction of the computing time.http://dx.doi.org/10.1155/2016/2357534 |
| spellingShingle | Maciej Pietrzyk Jan Kusiak Danuta Szeliga Łukasz Rauch Łukasz Sztangret Grzegorz Górecki Application of Metamodels to Identification of Metallic Materials Models Advances in Materials Science and Engineering |
| title | Application of Metamodels to Identification of Metallic Materials Models |
| title_full | Application of Metamodels to Identification of Metallic Materials Models |
| title_fullStr | Application of Metamodels to Identification of Metallic Materials Models |
| title_full_unstemmed | Application of Metamodels to Identification of Metallic Materials Models |
| title_short | Application of Metamodels to Identification of Metallic Materials Models |
| title_sort | application of metamodels to identification of metallic materials models |
| url | http://dx.doi.org/10.1155/2016/2357534 |
| work_keys_str_mv | AT maciejpietrzyk applicationofmetamodelstoidentificationofmetallicmaterialsmodels AT jankusiak applicationofmetamodelstoidentificationofmetallicmaterialsmodels AT danutaszeliga applicationofmetamodelstoidentificationofmetallicmaterialsmodels AT łukaszrauch applicationofmetamodelstoidentificationofmetallicmaterialsmodels AT łukaszsztangret applicationofmetamodelstoidentificationofmetallicmaterialsmodels AT grzegorzgorecki applicationofmetamodelstoidentificationofmetallicmaterialsmodels |