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Integral Recrystallization Modelling
作者姓名:G. Gottstein  V. Marx  R. Sebald Institut furr Metallkunde und Metallphysik  RWTH Aachen  Aachen  Germany
作者单位:G. Gottstein,V. Marx,R. Sebald Institut furr Metallkunde und Metallphysik,RWTH Aachen,52056 Aachen,Germany
摘    要:1.IntroductionAlthoughmancanproducemetallicmaterialssincemorethan5(X)0yearsitisafundamentalfindingofonlythiscenturythatthePropertiesofamaterialarenotdeterminedbyanymacroscopicquantity,likeoverallcomposition,dimensions,strainortemperature,ratherthanbyitsmicrostructure,i.e.thespatialdistributionofelements,phases,orientationsanddefects.Thismicrosmicture,however,isliabletOchangeduringprocessingofamaterialfromtheliquidstatetothefinalproduct,anditcanbesubstantiallyaffectedbychangingtheprocessingcon…


Integral Recrystallization Modelling
G. Gottstein,V. Marx,R. Sebald Institut furr Metallkunde und Metallphysik,RWTH Aachen, Aachen,Germany.Integral Recrystallization Modelling[J].Journal of Shanghai Jiaotong university,2000(1).
Authors:G Gottstein  V Marx  R Sebald Institut furr Metallkunde und Metallphysik  RWTH Aachen  Aachen  Germany
Institution:G. Gottstein,V. Marx,R. Sebald Institut furr Metallkunde und Metallphysik,RWTH Aachen,52056 Aachen,Germany
Abstract:We present models designed to represent the evolution of microstructure and crystallographic texture during recrystallization. For engineering applications the models are tied to a finite element approach. A connection to the deformed microstructure is established by dislocation theory of work hardening and Taylor type texture simulations. For temporal and spatial resolution a modified cellular automaton model was developed. A fast statistical approach for prediction of recrystallization kinetics and texture development discrete in time is presented. Predictions of the models are compared with experimental data.
Keywords:modelling  cellular automaton  statistical model  primary static recrystallization  recovery  crystallographic  orientation
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