Quasi-static and dynamic loading responses and constitutive modeling of titanium alloys

Khan, Akhtar S.; Suh, Young Ho; Kazmi, Rehan

doi:10.1016/j.ijplas.2003.06.005

Cited by 388 publications

(184 citation statements)

References 31 publications

Supporting

Mentioning

176

Contrasting

Unclassified

Order By: Relevance

“…This means that the energy balance equation governing temperature evolution should involve terms arising from a thermome chanical coupling. The thermodynamic process deviates from the isothermal conditions and approaches adiabaticity, leading to large variations in the temperature field (Liang and Khan, 1999;Khan et al, 2004). Also, forming and machining processes, used to elaborate components made of metastable austenitic steels, take place under non isothermal conditions (Hänsel et al, 1998;Miguélez et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

A constitutive model for analyzing martensite formation in austenitic steels deforming at high strain rates

Zaera

Rodríguez-Martínez

Casado³

et al. 2012

International Journal of Plasticity

View full text Add to dashboard Cite

a b s t r a c tThis study presents a constitutive model for steels exhibiting SIMT, based on previous sem inal works, and the corresponding methodology to estimate their parameters. The model includes temperature effects in the phase transformation kinetics, and in the softening of each solid phase through the use of a homogenization technique. The model was validated with experimental results of dynamic tensile tests on AISI 304 sheet steel specimens, and their predictions correlate well with the experimental evidence in terms of macroscopic stress strain curves and martensite volume fraction formed at high strain rates. The work shows the value of considering temperature effects in the modeling of metastable austen itic steels submitted to impact conditions. Regarding most of the works reported in the lit erature on SIMT, modeling of the martensitic transformation at high strain rates is the distinctive feature of the present paper.

show abstract

Section: Introductionmentioning

confidence: 99%

A constitutive model for analyzing martensite formation in austenitic steels deforming at high strain rates

Zaera

Rodríguez-Martínez

Casado³

et al. 2012

International Journal of Plasticity

View full text Add to dashboard Cite

show abstract

“…KHL model (Khan and Liang [23]; Khan et al [24]; Khan et al [25]) was used to model the experimental response of these materials. The KHL model is as follows:…”

Section: Constitutive Model and Theoretical Analysismentioning

confidence: 99%

Effect of Manufacturing Processes and Welding Type on Quasi-static and Dynamic Responses of Aluminum Alloys: Experiments and Modeling

Baig

Khan

Choi

et al. 2015

J. dynamic behavior mater.

Self Cite

View full text Add to dashboard Cite

Measured responses of two aluminum alloys over a wide range of strain-rates (10 -5 to 10 3 s -1 ) and temperatures are presented. The aluminum alloys include AA5182-O and AL6111-T4. A tensile spilt Hopkinson pressure bar was used for the dynamic experiments. The aluminum AA5182-O alloy (manufactured using continuous casting and direct chilling processes) including its first and second generation gas tungsten arc welded and friction stir welded TWB's exhibited negative strain-rate sensitivity. AL6111-T4 is found to have positive strain-rate sensitivity. The Khan-Huang-Liang constitutive model is shown to correlate and predict the observed responses reasonably well. The texture evolution of the AA5182-O and AL6111-T4 sheets during uniaxial tension is investigated using the EBSD technique and full-constraint polycrystal model. It is observed through the EBSD analysis that, the stable orientation is strongly dependent on the initial texture components.Keywords AA5182-O Á AL6111-T4 Á Quasi-static and dynamic response Á Tensile split Hopkinson bar Á EBSD

show abstract

“…Lin et al 18,19 and Quan et al 20 improved the initial Arrhenius-type equations by incorporating strain and some material parameters (such as structure factor A and activation energy of deformation Q) to obtain more accurate Arrhenius-type equation. Other phenomenological constitutive models involve the typical Johnson-Cook (JC) model and Khan-Huang-Liang (KHL) model etc., however, they exhibit large accuracy deviations at different strain rates and temperatures [21][22][23][24] . The phenomenological constitutive models cannot accurately track the highly non-linear hot flow behaviors at different strain rates and temperatures, and lack physical models of microscopic deformation mechanisms.…”

Section: Introductionmentioning

confidence: 99%

Numerical Description of Hot Flow Behaviors at Ti-6Al-2Zr-1Mo-1V Alloy By GA-SVR and Relative Applications

et al. 2016

View full text Add to dashboard Cite

Hot compression tests of as-cast Ti-6Al-2Zr-1Mo-1V alloy in a wide temperature range of 1073-1323 K and strain rate range of 0.01-10 s-1 were conducted by a servo-hydraulic and computer-controlled Gleeble-1500 machine. The hot flow behaviors of Ti-6Al-2Zr-1Mo-1V alloy show highly non-linear relationships with strain, strain rate and temperature. In order to accurately and effectively characterize the complex flow behaviors, support vector regression (SVR) which is a machine learning method was combined with Genetic Algorithm (GA) to characterize the flow behaviors, namely, the GA-SVR. The study abilities, generation abilities, and modeling efficiencies of the improved Arrhenius-type constitutive model, ANN, and GA-SVR for flow behaviors of as-cast Ti-6Al-2Zr-1Mo-1V alloy were detailedly compared. Comparison results show that the study ability of the GA-SVR is as strong as the ANN. The generation abilities and modeling efficiencies of these models were shown as follows in ascending order: the improved Arrhenius-type constitutive model < ANN < GA-SVR. Based on the established GA-SVR, the continuously three-dimensional relationships among flow stress, temperature, strain, and strain rate were constructed, which improve the simulation accuracy and related research fields where stress-strain data play important roles.

show abstract

Quasi-static and dynamic loading responses and constitutive modeling of titanium alloys

Cited by 388 publications

References 31 publications

A constitutive model for analyzing martensite formation in austenitic steels deforming at high strain rates

A constitutive model for analyzing martensite formation in austenitic steels deforming at high strain rates

Effect of Manufacturing Processes and Welding Type on Quasi-static and Dynamic Responses of Aluminum Alloys: Experiments and Modeling

Numerical Description of Hot Flow Behaviors at Ti-6Al-2Zr-1Mo-1V Alloy By GA-SVR and Relative Applications

Contact Info

Product

Resources

About