Model Assessment of an Open-Source Smoothed Particle Hydrodynamics (SPH) Simulation of a Vibration-Assisted Drilling Process

Minimum Quantity Lubrication (MQL) is a cooling and lubrication variant applied, for instance, in drilling processes. In the present approach, a new vibration-assisted drilling process is analyzed, which has considerable potential for manufacturing of extremely hard materials. Within this process, the MQL gas/liquid transport in the presence of a vibrating and rotating twist drill bit in the borehole is to be studied. Multiphase computational fluid dynamics is applied to analyze and optimize the MQL flow. However, applying conventional CFD methods with discretized continuum equations on a numerical grid is challenging in this process, as the vibrating drill bit frequently closes the gap in the borehole, where even dynamic grid application fails. The ability to use an open-source Smoothed Particle Hydrodynamics (SPH) meshless method to analyze the lubrication media flow is carried out to accurately and efficiently address this problem and overcome the severe limitations of conventional mesh-based methods. For a feasibility study of the method, the MQL air phase in the dynamic drill cavity is analyzed by SPH and validated against conventional CFD method results. The present study shows insufficient results of the SPH method, both in terms of solution plausibility and computational cost, for simulation of the problem at hand.

Automated summary

This article analyzes a new vibration-assisted drilling process for the manufacturing of extremely hard materials. It applies multiphase computational fluid dynamics to study the MQL gas/liquid transport in the presence of a vibrating and rotating twist drill bit. The article utilizes an open-source Smoothed Particle Hydrodynamics (SPH) meshless method to overcome the limitations of conventional mesh-based methods in analyzing lubrication media flow. However, the study finds that the SPH method does not provide satisfactory results in terms of solution plausibility and computational cost.