The article “A microstructure-integrated acoustoplastic constitutive model for ultrasonic-assisted machining of Ti6Al4V alloy” presents a novel modeling approach combining the Particle Finite Element Method (PFEM) with incremental homogeneous field distributions to predict both macro and micro responses of Ti6Al4V alloy during conventional machining (CM) and ultrasonic-assisted machining (UAM). scipedia.com
Key aspects of the study include:
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Microstructural Evolution: The model incrementally develops and incorporates microstructural parameters such as immobile and mobile dislocation densities, dynamic recrystallization grain size, and hardness into the PFEM using internal state variables. The Johnson–Mehl–Avrami–Kolmogorov (JMAK) model and Hall–Petch equation are employed to predict grain size and hardness, respectively.scipedia.com
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Acoustoplastic Constitutive Model: A microstructure-integrated acoustoplastic constitutive model is developed based on a modified Johnson–Cook model and average grain size predictions dependent on ultrasonic vibration parameters. This model is embedded into the PFEM to conduct thermo-mechanical analyses capable of capturing the alloy’s response, particularly in terms of serrated chip formation during CM and UAM processes.scipedia.com
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Validation: The model’s validity is checked through comparison with available experimental results in terms of chip shapes. Additionally, the predicted average grain size and hardness in serrated chips and machined surfaces are compared with experimental data, showing good agreement.scipedia.com
The study concludes that the proposed acoustoplastic constitutive model, coupled with microstructure and ultrasonic vibration parameters, can reliably analyze the CM and UAM processes of Ti6Al4V alloy, offering insights into the material behavior and mechanical response during machining.
H Bakhshan, E Oñate, JM Carbonell (2025). A microstructure-integrated acoustoplastic constitutive model for ultrasonic-assisted machining of Ti6Al4V alloy. CIRP Journal of Manufacturing Science and Technology 57, 14-31 https://doi.org/10.1016/j.cirpj.2024.12.007
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