2004
DOI: 10.1016/j.msea.2003.12.086
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Dislocation density based modeling of work hardening in the context of integrative modeling of aluminum processing

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Cited by 20 publications
(17 citation statements)
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“…2. At high temperatures however ( C 200 T°> ), and for alloys with much higher alloying contents, 3IVM had been proven to be more successful [1][2][3]. The quality of agreement is similar in the whole range of flow curves with C 200 T°≤ .…”
Section: Model Prediction For Low Temperaturesmentioning
confidence: 76%
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“…2. At high temperatures however ( C 200 T°> ), and for alloys with much higher alloying contents, 3IVM had been proven to be more successful [1][2][3]. The quality of agreement is similar in the whole range of flow curves with C 200 T°≤ .…”
Section: Model Prediction For Low Temperaturesmentioning
confidence: 76%
“…More detailed descriptions of the model 3IVM and its application in the FEM simulations are referred in [1][2][3]. More detailed descriptions of the model 3IVM and its application in the FEM simulations are referred in [1][2][3].…”
Section: Three Internal Variables Model -3ivmmentioning
confidence: 99%
“…When inserting the result for the Lagrangian multiplier λ ρ = − 1 (see ) into the evolution equation , the total dislocation density evolves according to The literature provides a variety of suggestions for the dislocation production rate, Q p , either based on continuum or micromechanical considerations (e.g., Gottstein and Argon , ; Goerdeler et al , ; Berdichevsky , ; Durinck et al , . Our main intention is to demonstrate the principle features of our model, the derived evolution equations.…”
Section: Modeling Recrystallizationmentioning
confidence: 94%
“…[10] A substantial number of previous approaches relying on a variety of experimental and analytical techniques have collected comprehensive observations on the kinetics of dynamic recrystallization [for a review see for example Humphrey and Hatherly, 1995]. These observations have led to the formulation of classical dislocation density based models [e.g., Kocks and Mecking, 1981;Gottstein and Argon, 1987;Goerdeler et al, 2004] and further attempts to derive plausible kinetic equations of state [e.g., Epstein and Maugin, 2002], both providing the basis for computer modeling with a range of calculation techniques [e.g., Song and Rettenmayr, 2007]. In several studies, the flow behavior of materials was modeled with a priori given grain structure [e.g., Kurzydlowski and Bucki, 1993;ter Heege et al, 2004;Berbenni et al, 2007] rather than modeling the evolution towards a recrystallized state.…”
Section: Plastic Flow and Recrystallization Phenomenamentioning
confidence: 99%
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