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• W2020322138 abstract "Because of the complex microstructures of crystalline materials exposed to commercial manufacturing processes it is up to now not possible to obtain fast and on-line simulations of crystallographic texture and anisotropy in the course of multiple deformation- and heat treatment procedures. In the present paper a hybrid approach for the on-line texture and anisotropy prediction will be developed for the fabrication of low alloyed ferritic steel sheets during cold rolling and subsequent annealing procedures. Our approach is based on two consecutive models: The first one is an artificial neuronal network (ANN) for the description of the rolling texture evolution. The second one is an analytical, Avrami-based texture component approach for the recrystallization. First results on low carbon steels will be presented." @default.
• W2020322138 created "2016-06-24" @default.
• W2020322138 creator A5004458930 @default.
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• W2020322138 date "2010-11-15" @default.
• W2020322138 modified "2023-09-25" @default.
• W2020322138 title "Fast, Physically-Based Algorithms for Online Calculations of Texture and Anisotropy during Fabrication of Steel Sheets" @default.
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• W2020322138 doi "https://doi.org/10.1002/adem.201000206" @default.
• W2020322138 hasPublicationYear "2010" @default.
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