Experimentally validated atomistic simulation of the effect of relevant grinding parameters on work piece topography, internal stresses, and microstructure

Abstract

In this work, we present a fully atomistic approach to modeling a finishing process with the goal to shed light on aspects of work piece development on the microscopic scale, which are difficult or even impossible to observe in experiments, but highly relevant for the resulting material behavior. In a large-scale simulative parametric study, we varied four of the most relevant grinding parameters: The work piece material, the abrasive shape, the temperature, and the infeed depth. In order to validate our model, we compared the normalized surface roughness, the power spectral densities, the steady-state contact stresses, and the microstructure with proportionally scaled macroscopic experimental results. Although the grain sizes vary by a factor of more than 1,000 between experiment and simulation, the characteristic process parameters were reasonably reproduced, to some extent even allowing predictions of surface quality degradation due to tool wear. Using the experimentally validated model, we studied time-resolved stress profiles within the ferrite/steel work piece as well as maps of the microstructural changes occurring in the near-surface regions. We found that blunt abrasives combined with elevated temperatures have the greatest and most complex impact on near-surface microstructure and stresses, as multiple processes are in mutual competition here.

Exploring the nano-polishing mechanisms of Invar

“…As the polishing speed increases, the maximum height of the chip accumulated in front of the abrasive and the MRR increase accordingly due to the higher plasticity of the work piece at higher temperatures [20]. However, when the polishing speed is higher than 150 m s -1 , the chip height decreases since more atoms in front of the abrasive flow back into the groove from the lateral sides.…”

“…Molecular dynamics (MD) simulations have been proven to be a powerful tool to investigate the material removal mechanism at atomic scale. The effects of polishing speed [14][15][16], polishing depth [17][18][19][20], rotating velocity [21,22], grain size [23,24], normal pressure [25][26][27] and crystal orientation [28] on the surface quality of the work piece have been systematically investigated based on MD simulations. Zhang et al [29] studied the effects of grinding depths and speeds on the subsurface damage layer (SDL).…”

Towards a multi-abrasive grinding model for the material point method

“…Grinding is an extremely complicated process, which is affected by a number of parameters, such as the material of the abrasives and the work piece as well as their microstructure, the pressure, the temperature, the geometry and orientation of the abrasives, as well as the cutting speed and other machine parameters (Gopal and Rao, 2003;Eder et al, 2022;Wang et al, 2022). Often the correct operation of the grinding process can be determined by the existence and the shape of the formed chips (Rasim et al, 2015;Karasawa et al, 2019).…”

Does speed kill or make friction better? — Designing materials for high velocity sliding

“…Even though not universal, the general trend is that friction decreases with increasing speed. Such considerations are of interest for applications and processes where high speeds and high shear rates prevail, including brakes, clutches, crash performance of automotive components [12], high-speed metal fabrication [13], turbine engines [14], explosive welding [15], gun barrels [16], but recently also in the field of electromobility for high-speed electrical motors [17]. De-Graphical Abstract spite all these processes being grouped under the term "high-speed dynamics", typical sliding velocities cover several orders of magnitude with different deformation mechanisms being dominant [18,19].…”

“…Molecular dynamics (MD) simulations, paired with modern high-performance computing facilities, can nowadays handle systems with tens to hundreds of millions of atoms for reasonable time periods (some tens of nanoseconds) [38], allowing an analysis of microstructural processes at the atomic level [39,31]. This leads to more and more possibilities to directly compare MD results with real experimental data [40,13]. MD can provide an ideal vehicle for the description of plastic deformations and to study how dislocations, twins, and grain boundaries behave collectively.…”