What is it about?

This paper simulates the temperature-dependent dynamic viscosity of the cutting fluid’s flow, thus analysing the approximated real behaviour in a simplified model. In order to take the heat transfer between the workpiece and the cutting fluid into account, the Finite Element Method (FEM) was bidirectionally coupled. A mathematical formula for determining the dynamic viscosity of the cutting fluid as a function of temperature was used for the temperature evolution. Simulations were performed using the standard k-ω-SST, k-ω-SST-SAS, and k-ω-SST-DES turbulence models for comparison. The results show that the influence of dynamic viscosity and temperature plays an important role and should therefore not be neglected in process simulations. For example, increasing the temperature from T = 25 °C to T = 150 °C reduced viscosity by 95%. The modelling approach presented here is suitable for future analysis simulations and can be applied not only to different drill geometries but also to numerous machining processes where dynamic viscosity plays an important role.

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Why is it important?

The results show how important it is to consider dynamic viscosity in simulations and demonstrate an efficient approach. In addition, different turbulence models are compared with each other in order to qualify the accuracy of the results.

Perspectives

In this article I show important new approaches that have strong potential for the future. In addition, this field of research is one of my areas of expertise, which has already been used to solve numerous challenges. The understanding between CFD and mechanical engineering in general is still a long way to go. In contrast to FEM, CFD is still far from being part of everyday practice, as there are still many gaps in understanding and application.

Dr. Ekrem Oezkaya
Recep Tayyip Erdogan Universitesi

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This page is a summary of: Numerical fluid structure simulation analysis of temperature-dependent dynamic viscosity with a simplified deep drilling model, International Journal of Modelling and Simulation, October 2024, Taylor & Francis,
DOI: 10.1080/02286203.2024.2414952.
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