An MD study of the wear of defective tools in the nanometric cutting process with workpiece thickness = 20 units

Introduction

An MD simulation analysis was conducted to compare the cutting response and the tool wear between flawed and flawless tool surfaces based on a three-layer nanometric cutting model.

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Methodology

Materials

• single diamond tool, with dimensions 11[100] 11[010] 22[001] in x, y, and z directions, edge radius = 4 x diamond unit cell
• 3C-SiC workpiece, with dimensions 65[010] 20[010] 18[001] in x, y, and z directions

Cutting Conditions

• Depth of cut = 5 x 3C-SiC unit cell length
• Cutting direction = [010]<-1 0 0> for ≈200 Å
• Initial temperature = 300 K

Simultion Settings

1. Equilibration

• NVT ensemble, timestep = 0.001 ps (1 fs) for 24000 steps

2. Cutting

• NVT+NVE ensembles, timestep = 0.0005 ps (0.5 fs) for 133000 steps

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Execution

Input Template:

• in.cutsic_eq.lmp

Potential

• EA Scr === pair_style atomistica BrennerScr

Variables

• v cutting velocity (unit = Å/ps)
• grooveDepth Depth of V-shaped groove defect on the diamond flank face (Range: [0-9], unit = length of a diamond unit cell)
• grooveTan Angle of V-shaped groove defect on the diamond flank face in tangent (e.g. input 1 for 45 degrees, 0.5 for 26.56(5) degrees)

example:

@Precision > mpirun -np 32 ../../lmp_mpi_20161117_atomistica046 < in.cutsic_eq.lmp -v v 3.0 -v grooveDepth 0 -v grooveTan 1.0

Citations and References

• If you utilize the materials in this repository, please cite the following paper:

  Fung, K. Y., Tang, C. Y., & Cheung, C. F. (2017). Molecular dynamics analysis of the effect of surface flaws of diamond tools on tool wear in nanometric cutting. Computational Materials Science, 133, 60-70.

• If you work with earlier versions of LAMMPS, please reference:

  Plimpton, S. (1995). Fast Parallel Algorithms for Short-Range Molecular Dynamics. Journal of Computational Physics, 117, 1-19.

  For further details and citations for later versions of LAMMPS, please refer to the LAMMPS citation guidelines.

• If you publish results obtained using OVITO, please cite the following software in your publication:

  Stukowski, A. (2010). Visualization and analysis of atomistic simulation data with OVITO - the Open Visualization Tool. Modelling and Simulation in Materials Science and Engineering, 18, 015012.

  For additional information, please refer to the OVITO citation guidelines.

• For the atomic potential utilized in the MD simulations, please reference:

  Erhart, P., & Albe, K. (2005). Analytical potential for atomistic simulations of silicon, carbon, and silicon carbide. Physical Review B, 71(3), 035211.

  Pastewka, L., Klemenz, A., Gumbsch, P., & Moseler, M. (2013). Screened empirical bond-order potential for Si-C. Physical Review B, 87, 205410.

  Pastewka, L., Mrovec, M., Moseler, M., & Gumbsch, P. (2012). Bond order potentials for fracture, wear, and plasticity. MRS Bulletin, 37, 493.