Prediction of hot compression flow curves of Ti–6Al–4V alloy in α+β phase region

Shafaat, Mohammad Amin; Omidvar, Hamid; Fallah, Behzad

doi:10.1016/j.matdes.2011.06.048

Cited by 49 publications

(28 citation statements)

References 21 publications

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“…ε is the strain rate (s −1 ), Q is the activation energy of hot deformation (kJ·mol −1 ), R is the universal gas constant (8.3145 J·mol −1 ·K −1 ), T is the absolute temperature (K), and σ is flow stress (MPa), A, n´, β, α and n are the material constants, α = β/n´ [29]. The stress multiplier α is an adjustable constant that brings ασ into the correct range that gives linear and parallel lines in ln .…”

Section: Strain Compensated Arrhenius-type Constitutive Modelmentioning

confidence: 99%

Correction of Flow Curves and Constitutive Modelling of a Ti-6Al-4V Alloy

Dong

Zhang

et al. 2018

Metals

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Abstract:Isothermal uniaxial compressions of a Ti-6Al-4V alloy were carried out in the temperature range of 800-1050 • C and strain rate range of 0.001-1 s −1 . The effects of friction between the specimen and anvils as well as the increase in temperature caused by the high strain rate deformation were considered, and flow curves were corrected as a result. Constitutive models were discussed based on the corrected flow curves. The correlation coefficient and average absolute relative error for the strain compensated Arrhenius-type constitutive model are 0.986 and 9.168%, respectively, while the values for a modified Johnson-Cook constitutive model are 0.924 and 22.673%, respectively. Therefore, the strain compensated Arrhenius-type constitutive model has a better prediction capability than a modified Johnson-Cook constitutive model.

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Section: Strain Compensated Arrhenius-type Constitutive Modelmentioning

confidence: 99%

Correction of Flow Curves and Constitutive Modelling of a Ti-6Al-4V Alloy

Dong

Zhang

et al. 2018

Metals

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“…Shafaat et al (2011) proposed an empirical flow stress model for Ti-6Al-4V by combining the Cingara model during hardening up to the peak stress and a softening model identical to JMAK equation thereafter. A similar approach was followed by Karpat (2011) by mixing a modified Johnson-Cook model for hardening and a hyperbolic model for softening which is used during machining simulation of Ti-6Al-4V.…”

Section: State Of the Art In Models For Ti-6al-4vmentioning

confidence: 99%

A model for Ti–6Al–4V microstructure evolution for arbitrary temperature changes

Murgau

Pederson

Lindgren

2012

Modelling Simul. Mater. Sci. Eng.

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This thesis is devoted to microstructure modelling of Ti-6Al-4V. The microstructure and the mechanical properties of titanium alloys are highly dependent on the temperature history experienced by the material. The developed microstructure model accounts for thermal driving forces and is applicable for general temperature histories. It has been applied to study wire feed additive manufacturing processes that induce repetitive heating and cooling cycles. The microstructure model adopts internal state variables to represent the microstructure through microstructure constituents' fractions in finite element simulation. This makes it possible to apply the model efficiently for large computational models of general thermomechanical processes. The model is calibrated and validated versus literature data. It is applied to Gas Tungsten Arc Welding -also known as Tungsten Inert Gas welding-wire feed additive manufacturing process. Four quantities are calculated in the model: the volume fraction of phase, consisting of Widmanstätten , grain boundary , and martensite . The phase transformations during cooling are modelled based on diffusional theory described by a Johnson-Mehl-AvramiKolmogorov formulation, except for diffusionless martensite formation where the Koistinen-Marburger equation is used. A parabolic growth rate equation is used for the to transformation upon heating. An added variable, structure size indicator of Widmanstätten , has also been implemented and calibrated. It is written in a simple Arrhenius format. The microstructure model is applied to in finite element simulation of wire feed additive manufacturing. Finally, coupling with a physically based constitutive model enables a comprehensive and predictive model of the properties that evolve during processing.

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“…Although the software pack has a built-in material library that includes Ti-6Al-4V titanium alloy, for this research, the authors collected literature data regarding the flow stress curves in a temperature range from 25 to 1200 • C and strain rate range from 0.001 to 1000 s −1 [27,19,[28][29][30], with a range of stress values from 1400 to 25 MPa. An example of the mechanical data collected by the authors is shown in Fig.…”

Section: Transformation Model Set-up and Tuningmentioning

confidence: 99%