Modeling the flow behavior, recrystallization, and crystallographic texture in hot-deformed Fe-30 Wt pct ni austenite
The present work describes a hybrid modeling approach developed for predicting the flow behavior, recrystallization characteristics, and crystallographic texture evolution in a Fe-30 wt pct Ni austenitic model alloy subjected to hot plane strain compression. A series of compression tests were perfor...
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| Veröffentlicht in: | Metallurgical and materials transactions. A, Physical metallurgy and materials science Physical metallurgy and materials science, 2007-10, Vol.38 (10), p.2400-2409 |
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| container_title | Metallurgical and materials transactions. A, Physical metallurgy and materials science |
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| creator | ABBOD, M. F SELLARS, C. M CIZEK, P LINKENS, D. A MAHFOUF, M |
| description | The present work describes a hybrid modeling approach developed for predicting the flow behavior, recrystallization characteristics, and crystallographic texture evolution in a Fe-30 wt pct Ni austenitic model alloy subjected to hot plane strain compression. A series of compression tests were performed at temperatures between 850 °C and 1050 °C and strain rates between 0.1 and 10 s^sup -1^. The evolution of grain structure, crystallographic texture, and dislocation substructure was characterized in detail for a deformation temperature of 950 °C and strain rates of 0.1 and 10 s^sup -1^, using electron backscatter diffraction and transmission electron microscopy. The hybrid modeling method utilizes a combination of empirical, physically-based, and neuro-fuzzy models. The flow stress is described as a function of the applied variables of strain rate and temperature using an empirical model. The recrystallization behavior is predicted from the measured microstructural state variables of internal dislocation density, subgrain size, and misorientation between subgrains using a physically-based model. The texture evolution is modeled using artificial neural networks. [PUBLICATION ABSTRACT] |
| doi_str_mv | 10.1007/s11661-007-9292-5 |
| format | Article |
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F ; SELLARS, C. M ; CIZEK, P ; LINKENS, D. A ; MAHFOUF, M</creator><creatorcontrib>ABBOD, M. F ; SELLARS, C. M ; CIZEK, P ; LINKENS, D. A ; MAHFOUF, M</creatorcontrib><description>The present work describes a hybrid modeling approach developed for predicting the flow behavior, recrystallization characteristics, and crystallographic texture evolution in a Fe-30 wt pct Ni austenitic model alloy subjected to hot plane strain compression. A series of compression tests were performed at temperatures between 850 °C and 1050 °C and strain rates between 0.1 and 10 s^sup -1^. The evolution of grain structure, crystallographic texture, and dislocation substructure was characterized in detail for a deformation temperature of 950 °C and strain rates of 0.1 and 10 s^sup -1^, using electron backscatter diffraction and transmission electron microscopy. The hybrid modeling method utilizes a combination of empirical, physically-based, and neuro-fuzzy models. The flow stress is described as a function of the applied variables of strain rate and temperature using an empirical model. The recrystallization behavior is predicted from the measured microstructural state variables of internal dislocation density, subgrain size, and misorientation between subgrains using a physically-based model. The texture evolution is modeled using artificial neural networks. [PUBLICATION ABSTRACT]</description><identifier>ISSN: 1073-5623</identifier><identifier>EISSN: 1543-1940</identifier><identifier>DOI: 10.1007/s11661-007-9292-5</identifier><identifier>CODEN: MMTAEB</identifier><language>eng</language><publisher>New York, NY: Springer</publisher><subject>Alloys ; Applied sciences ; Crystallography ; Electron microscopes ; Exact sciences and technology ; Grain size ; Heat transfer ; Metallurgy ; Metals. 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The evolution of grain structure, crystallographic texture, and dislocation substructure was characterized in detail for a deformation temperature of 950 °C and strain rates of 0.1 and 10 s^sup -1^, using electron backscatter diffraction and transmission electron microscopy. The hybrid modeling method utilizes a combination of empirical, physically-based, and neuro-fuzzy models. The flow stress is described as a function of the applied variables of strain rate and temperature using an empirical model. The recrystallization behavior is predicted from the measured microstructural state variables of internal dislocation density, subgrain size, and misorientation between subgrains using a physically-based model. The texture evolution is modeled using artificial neural networks. 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A, Physical metallurgy and materials science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>ABBOD, M. F</au><au>SELLARS, C. M</au><au>CIZEK, P</au><au>LINKENS, D. A</au><au>MAHFOUF, M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modeling the flow behavior, recrystallization, and crystallographic texture in hot-deformed Fe-30 Wt pct ni austenite</atitle><jtitle>Metallurgical and materials transactions. A, Physical metallurgy and materials science</jtitle><date>2007-10-01</date><risdate>2007</risdate><volume>38</volume><issue>10</issue><spage>2400</spage><epage>2409</epage><pages>2400-2409</pages><issn>1073-5623</issn><eissn>1543-1940</eissn><coden>MMTAEB</coden><abstract>The present work describes a hybrid modeling approach developed for predicting the flow behavior, recrystallization characteristics, and crystallographic texture evolution in a Fe-30 wt pct Ni austenitic model alloy subjected to hot plane strain compression. A series of compression tests were performed at temperatures between 850 °C and 1050 °C and strain rates between 0.1 and 10 s^sup -1^. The evolution of grain structure, crystallographic texture, and dislocation substructure was characterized in detail for a deformation temperature of 950 °C and strain rates of 0.1 and 10 s^sup -1^, using electron backscatter diffraction and transmission electron microscopy. The hybrid modeling method utilizes a combination of empirical, physically-based, and neuro-fuzzy models. The flow stress is described as a function of the applied variables of strain rate and temperature using an empirical model. The recrystallization behavior is predicted from the measured microstructural state variables of internal dislocation density, subgrain size, and misorientation between subgrains using a physically-based model. The texture evolution is modeled using artificial neural networks. [PUBLICATION ABSTRACT]</abstract><cop>New York, NY</cop><pub>Springer</pub><doi>10.1007/s11661-007-9292-5</doi><tpages>10</tpages></addata></record> |
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| subjects | Alloys Applied sciences Crystallography Electron microscopes Exact sciences and technology Grain size Heat transfer Metallurgy Metals. Metallurgy Plastic deformation Stress-strain curves Temperature Transmission electron microscopy |
| title | Modeling the flow behavior, recrystallization, and crystallographic texture in hot-deformed Fe-30 Wt pct ni austenite |
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