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Fast, Physically‐Based Algorithms for Online Calculations of Texture and Anisotropy during Fabrication of Steel Sheets
Author(s) -
Winning Myrjam,
Raabe Dierk
Publication year - 2010
Publication title -
advanced engineering materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 114
eISSN - 1527-2648
pISSN - 1438-1656
DOI - 10.1002/adem.201000206
Subject(s) - materials science , anisotropy , recrystallization (geology) , fabrication , annealing (glass) , microstructure , texture (cosmology) , deep drawing , metallurgy , algorithm , composite material , computer science , artificial intelligence , optics , physics , image (mathematics) , medicine , paleontology , alternative medicine , pathology , biology
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.