Numerical modeling of laser assisted machining of a beta titanium alloy
[Display omitted] •SPH method is used to develop the machining model.•The simulation results were validated by experiments.•Laser assisted machining of beta titanium alloy Ti–6Cr–5Mo–5V–4Al was studied.•Two material constitutive models have been evaluated in the machining simulation. Laser assisted...
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Veröffentlicht in: | Computational materials science 2014-09, Vol.92, p.149-156 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | [Display omitted]
•SPH method is used to develop the machining model.•The simulation results were validated by experiments.•Laser assisted machining of beta titanium alloy Ti–6Cr–5Mo–5V–4Al was studied.•Two material constitutive models have been evaluated in the machining simulation.
Laser assisted machining is a promising new machining technology that can be used to assist with the fabrication of components from difficult to machine materials such as beta titanium alloys. To understand the mechanism behind this process, a reliable numerical machining model is needed. This study employed an SPH method to the problem of laser assisted machining of Ti–6Cr–5Mo–5V–4Al alloy. The SPH method has several advantages when dealing with large-deformation problems compared with traditional finite element methods. A laser scanning model was developed beforehand to predict the temperature elevation due to laser heating and the temperature results were used as initial conditions for the SPH/FE machining models. Johnson–Cook parameters and Zerilli–Armstrong parameters of Ti–6Cr–5Mo–5V–4Al alloy were acquired based on experimental data from the Split Hopkinson Pressure Bar (SHPB) test and were implemented in the machining models. The cutting force predictions of machining models using these two material models were discussed in this study. Both conventional machining (CM) and laser assisted machining (LAM) were simulated. The main cutting force predictions and the temperature predictions were compared with experimental results to validate the models. |
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ISSN: | 0927-0256 1879-0801 |
DOI: | 10.1016/j.commatsci.2014.05.023 |