کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
491923 | 721031 | 2015 | 14 صفحه PDF | دانلود رایگان |
• Experimental optimization of the cutting process is time consuming and expensive.
• Numerical modelling with FEM is an alternative but computing time is too high.
• Mass scaling allows to speed up the calculations by reducing computing time by 70%.
• Mass scaling does not degrade the quality of the results significantly.
• Numerical influence on the model is very low.
Machining by chips removal operations depend on a large set of parameters, which leads to a time consuming and expensive experimental optimization of this process. Numerical finite element modelling of orthogonal cutting is its most attractive alternative at this time. Apart from the difficulties caused by the complexity of the phenomena involved, the industrial application of this method comes up against unacceptable CPU computing time. The mass scaling is a numerical technique allowing to artificially speed up these calculations. This paper presents its application to a Lagrangian orthogonal cutting finite element model of the most commonly machined titanium alloy, Ti6Al4V, which has not previously been performed. Once the adaptive mass scaling is enabled, the CPU computing time is reduced by about 70% for a typical computation. This improvement should not be performed at the expense of the quality of the results by comparison to the experimental reference (chip morphology, formation mechanism, cutting forces, teeth formation frequency, etc.), nor impact significantly the numerical computation (total mass increase of the model, for example). This study shows that, when used carefully, the adaptive mass scaling constitutes an efficient method to reduce the CPU computation time. It should therefore be considered for the development of future models.
Journal: Simulation Modelling Practice and Theory - Volume 53, April 2015, Pages 1–14