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Research Article

Metal chip transport through narrow twisted drill channels—Coupling of CFD and DEM

Teresa Tonn1( )Lukas Schumski1Jens Sölter1,2,3Lizoel Buss1Anne Geppert1,2,3Bernhard Karpuschewski1,2,3Udo Fritsching1,2,3
Leibniz-Institute for Materials Engineering IWT, Badgasteiner Str. 3, Bremen 28359, Germany
Faculty of Production Engineering, University of Bremen, Bibliothekstr. 1, Bremen 28359, Germany
MAPEX Center for Materials and Processes, University of Bremen, Bremen 28359, Germany
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Abstract

In drilling processes, chips must be transported out of the borehole to free the work site from obstructions and evacuate process heat to prevent tool damage/breakage and thermal influences on the workpiece material. In vibration-assisted drilling (VAD), an axial tool oscillation superimposed on the continuous tool feed improves the chip transport by a kinematically enforced chip breakage. Nevertheless, especially for ductile and adhesive materials, clogging of the tool flute by subsequently generated chips is still a challenge. This study investigates the chip transport process in VAD under minimum quantity lubrication (MQL) using a coupled CFD–DEM simulation approach. The influence of process and chip properties as well as model parameters (here, the coefficients of friction and restitution) on the chip transport behavior within the tool flute have been analyzed. Experimental high-speed video analyses served to validate key model features and confirm overall trends. The simulation results reveal that chip velocity and transport behavior are strongly influenced by friction, drill rotation, and chip geometry. Higher velocities and chip rotation increase the risk of chip jamming in the flute. The coupled model and simulation results provide valuable insight into chip-flow interactions and support future tool and process design.

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Experimental and Computational Multiphase Flow
Pages 657-668

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Cite this article:
Tonn T, Schumski L, Sölter J, et al. Metal chip transport through narrow twisted drill channels—Coupling of CFD and DEM. Experimental and Computational Multiphase Flow, 2026, 8(4): 657-668. https://doi.org/10.1007/s42757-025-0284-8

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Received: 08 July 2025
Revised: 15 November 2025
Accepted: 30 November 2025
Published: 10 September 2026
© Tsinghua University Press 2026