2013
DOI: 10.1590/s1516-14392013005000149
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Compressive deformation behavior modeling of AZ31 magnesium alloy at elevated temperature considering the strain effect

Abstract: The true stress-strain data from isothermal hot compression tests, in the temperature range of 300-500 °C and strain rate of 0.001-0.1s -1, were employed to study the flow behavior of AZ31 and to develop constitutive equation based on an Arrhenius-type equation. The flow stress increases with the decrease of deformation temperature and the increase of strain rate, which can be represented by Zener-Hollomon parameter in an exponential equation. The influence of strain was incorporated in the developed constitut… Show more

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Cited by 16 publications
(5 citation statements)
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“…Considering the effects of strain on material parameters, Lin et al (Ref 15) proposed an improved Arrhenius-type equation to describe the deformation behaviors of 42CrMo steel over wide ranges of strain rate and deformation temperature. Furthermore, this constitutive model has been successfully verified by some other alloys, such as magnesium alloys (Ref 16,17) developed the physically based constitutive equations for describing the work hardening-dynamic recovery and dynamic recrystallization behaviors of some typical alloys. In addition, some neural network models for alloys were established to predict hot deformation behaviors of some typical alloys, such as 42CrMo steel (Ref 39) and Al-Zn-Mg alloy (Ref 40).…”
Section: Introductionmentioning
confidence: 88%
“…Considering the effects of strain on material parameters, Lin et al (Ref 15) proposed an improved Arrhenius-type equation to describe the deformation behaviors of 42CrMo steel over wide ranges of strain rate and deformation temperature. Furthermore, this constitutive model has been successfully verified by some other alloys, such as magnesium alloys (Ref 16,17) developed the physically based constitutive equations for describing the work hardening-dynamic recovery and dynamic recrystallization behaviors of some typical alloys. In addition, some neural network models for alloys were established to predict hot deformation behaviors of some typical alloys, such as 42CrMo steel (Ref 39) and Al-Zn-Mg alloy (Ref 40).…”
Section: Introductionmentioning
confidence: 88%
“…8, 9 and 10. This type of approach was also applied by Quan et al [23], [18] 5.23 145 Nourollahi et al [19] 3.5 145 Bhattacharya et al [20] 5.5…”
Section: Dynamic Recrystallized Volume Fractionmentioning
confidence: 98%
“…Therefore, it is believed that plastic strain has a minor effect in this particular case. [33] The parameters related to the chemical free energy in Eqs. ( 4) and ( 5) are determined by physical analysis or experimental data from real AZ31 alloy, and we use the method described in our recent studies to obtain the parameters values.…”
Section: Model Descriptionmentioning
confidence: 99%