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Optimization of Forging Process Parameters and Prediction Model of Residual Stress of Ti‐6Al‐4V Alloy

Xiurong Fang, Liu Liu, Jia Lü, Yang Gao

2021Advances in Materials Science and Engineering16 citationsDOIOpen Access PDF

Abstract

Nonisothermal forging is an efficient plastic forming method for titanium alloys, but at the same time, it can produce large and uneven residual stress, which seriously affects the service life of components. In order to quantitatively analyze the influence of forging process parameters on the residual stress of Ti‐6Al‐4V alloy forgings, a numerical model was first established and optimized in combination with experiments. Then, the effects of deformation temperature, deformation degree, and deformation speed on the residual stress of forgings were analyzed by orthogonal test, and the optimal combination of forging process parameters was obtained. Finally, the multiple regression analysis was employed to propose multivariate regression models for the prediction of the average equivalent residual stress. Results show that the prediction model can be used for predicting the residual stress of Ti‐6Al‐4V alloy forgings with a higher reliability.

Topics & Concepts

Materials scienceResidual stressForgingAlloyProcess (computing)MetallurgyTitanium alloyResidualStress (linguistics)AlgorithmComputer sciencePhilosophyLinguisticsOperating systemTitanium Alloys Microstructure and PropertiesMetallurgy and Material FormingWelding Techniques and Residual Stresses
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