A modified constitutive equation for elevated temperature flow behavior of Ti-6Al-4V alloy based on double multiple nonlinear regression

Zhanwei Yuan, Fuguo Li, Huijuan Qiao, Meili Xiao, Jun Cai, Jiang Li

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

Constitutive analysis for hot working of Ti-6Al-4V alloy was carried out utilizing experimental stress-strain data from isothermal hot compression tests, in a wide range of temperatures (1073-1323K), strains (0.1-0.5) and strain rates (0.0005-1s-1). A modified constitutive equation based on multiple nonlinear regression (DMNR) has been established considering the independent effects of strain, strain rate, temperature and their interrelation. A comparative study has been made on the capability of strain-compensated Arrhenius-type Constitutive Model (SACM), orthogonal experiment and Variance Analysis Constitutive Model (OVCM) and DMNR model. Suitability of these models was evaluated by comparing the correlation coefficient, average absolute relative error and statistical analysis. It is observed that the OVCM is not suitable in providing good description of flow behavior of Ti-6Al-4V alloy in the above hot working domain. Predictions of the other two models are in close agreement with the experimental data. However, the DMNR model was based on the test data scatter plot which did not need a specific constitutive form in advance and had a lower standard deviation. It indicates that the developed constitutive equation considering the coupling effects among strain, strain rate and deformation temperature can predict flow stress of Ti-6Al-4V alloy with good correlation and generalization.

Original languageEnglish
Pages (from-to)260-270
Number of pages11
JournalMaterials Science and Engineering: A
Volume578
DOIs
StatePublished - 20 Aug 2013

Keywords

  • Constitutive equation
  • Non-ferrous metals and alloy
  • Plastic behavior

Fingerprint

Dive into the research topics of 'A modified constitutive equation for elevated temperature flow behavior of Ti-6Al-4V alloy based on double multiple nonlinear regression'. Together they form a unique fingerprint.

Cite this