An insight into texture evolution and tailoring during multi-pass cold pilgering of high-strength titanium alloy tubular materials

The high-strength titanium alloy tubular materials are extensively applied in aviation and aerospace industries, wherein the mechanical properties, subsequent formability and in-service performance of the tube are strongly dependent on the texture variation. Cold pilgering has been a favorable fabrication technology for hard-to-deform tubes, however, the coupling effects of inherently low symmetric and complex multi-pass thermal-mechanical histories led to the significant diversity of the texture evolution of high-strength titanium alloy tubular materials. The traditional methods which mainly dependent on the Q value and deformation degree adjusting are difficult to achieve the precise tailoring of texture in multi-pass cold pilgering process. In this work, to break the limitation of the traditional method, by taking into account the mechanical properties iterating in each pass and the texture inheritance in recrystallization annealing process, a numerical computation platform for texture evolution prediction during multi-pass cold pilgering of titanium alloy tube was firstly established. The accuracy and reliability of the platform was verified by the 3-pass cold pilgering experiment and texture characterization. Secondly, the crucially effect of the initial texture was deeply explored in this work, the results indicated that the desired radial texture would be enhanced only when the Q value and area reduction ratio (AR) exceed the corresponding threshold under the specific initial texture, in which the tensile twinning was the vital deformation mode for the grain rotation and texture evolution. Thirdly, the quantitative correlation between processing conditions and finished radial texture intensity f_RD was established which comprehensively introduced the Q value, AR and initial texture intensity. In contrast to the accuracy of 59.4% based on the single factor Q value and 75.1% based on double factor of Q value and AR, the prediction accuracy of the quantitative correlation established in this work upgraded to approximate to 95%. Finally, taking the contractile strain ratio (CSR) as the index to reflect the macro anisotropy mechanical properties, the bonds that unite the processing conditions, f_RD and CSR were also built.