A microstructure-integrated acoustoplastic constitutive model for ultrasonic-assisted machining of Ti6Al4V alloy

Abstract

The ultrasonic-assisted machining (UAM) technology, compared to conventional machining (CM), has been proven to be an effective method for machining the difficult-to-cut Ti6Al4V alloy (TC4). In the UAM process, the evolution mechanism of microstructure and hardness directly influences the material behavior and consequently, mechanical response, which remains unrevealed from a computational perspective. To address this, in this study, we present a developed modeling technique that combines the Particle Finite Element Method (PFEM) with incremental homogeneous field distributions in a coupled manner to effectively predict the macro and micro response of the material in both CM and UAM processes. First, the evolution of microstructural parameters, including immobile dislocation density (IDD) and mobile dislocation density (MDD), dynamic recrystallization (DRx) grain size, and hardness, is incrementally developed and incorporated into the PFEM using internal state variables. The Johnson–Mehl–Avrami–Kolmogorov (JMAK) model and Hall–Petch equation are employed for predicting grain size and hardness, respectively. Second, A microstructure-integrated acoustoplastic constitutive model is developed based on a modified Johnson–Cook (JC) model and average grain size (AGS) predictions dependent on ultrasonic vibration (UV) parameters. The proposed model is embedded into the PFEM to conduct a thermo-mechanical analysis capable of capturing the TC4 response, particularly in terms of serrated chip formation during CM and UAM processes. The model’s validity is checked through comparison with available experimental results in terms of chip shapes. Lastly, the predicted AGS and hardness in serrated chips and machined surface are compared with experimental data, showing good agreement. This suggests that the proposed acoustoplastic constitutive model, coupled with microstructure and UV parameters, can reliably analyze the CM and UAM processes of the TC4.