Dynamic characterization and vibration response of high-speed milling for A2024-T351 aluminum alloy
Abstract
A coupled finite element–finite difference framework was developed to simulate high-speed peripheral milling of A2024-T351 aluminum alloy, enabling the analysis of chip formation, thermal gradients, and dynamic instability. The finite element model was used to predict the thermo-mechanical response and chip formation, while the finite difference formulation was employed to solve the transient heat transfer under different cutting conditions. The workpiece plastic deformation was described using a Johnson–Cook (JC) constitutive law coupled with a cumulative damage model, whereas the tungsten carbide (WC) cutting tool was modeled as a thermo-elastic body. Mesh and time-step sensitivity analyses were performed to ensure numerical convergence and solution stability. Thermal fields and structural responses were evaluated as functions of cutting speed, feed rate, depth of cut, and milling strategy (climb and conventional). Time-resolved cutting force signals were analyzed using the fast Fourier transform (FFT) to correlate local chip segmentation with macroscopic vibration modes. The results showed that the maximum temperature stabilized after the engagement of the fourth tooth (739.6–742.5 K), with the majority of generated heat dissipated through chip evacuation. Compared with conventional milling, climb milling reduced the peak contact temperature by 6.5% and resulted in a smoother harmonic force response. Spectral analysis further showed a clear separation between the tooth-passing frequency (600 Hz) and the thermomechanical chip segmentation frequency (1,850 Hz). The numerical predictions were validated against experimental cutting parameter measurements, showing deviations below 5%. The proposed framework provides an effective predictive tool for analyzing high-speed milling and identifying cutting conditions that reduce structural vibration while maintaining thermal and mechanical performance.
Copyright (c) 2026 Rami Smari, Ltaief lammari, Ali Rakrouk, Ali Arfaoui, Sana BenKhlifa

This work is licensed under a Creative Commons Attribution 4.0 International License.
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