Surface Metrology Principles for Snow and Ice Friction Studies

Recent advances in surface metrology science are applied to understanding friction with snow and ice. Conventional surface metrology’s measurement, analyses, and characterizations, have inherent limitations for elucidating tribological interactions. Strong functional correlations and confident discriminations with slider surface topographies, textures, or “roughness”, have largely eluded researchers using conventional methods. Building on 4 decades of research using multiscale geometric methods, two surface metrology axioms and corollaries are proposed with good potential to provide new technological insights.

Surface Hierarchy: Macroscopic and Microscopic Design Elements for Improved Sliding on Ice

Frictional interaction with a surface will depend on the features and topography within the contact zone. Describing this interaction is particularly complex when considering ice friction, which needs to look at both the macroscopic and microscopic levels. Since Leonardo da Vinci shared his findings that roughness increases friction, emphasis has been placed on measuring surface coarseness, neglecting the contact area. Here, a profilometer was used to measure the contact area at different slicing depths and identify contact points. Metal blocks were polished to a curved surface to reduce the contact area; further reduced by milling 400 µm grooves or laser-micromachining grooves with widths of 50 µm, 100 µm, and 150 µm. Sliding speed was measured on an inclined ice track. Asperities from pileup reduced sliding speed, but a smaller contact area from grooves and a curved sliding surface increased sliding speed. An analysis of sliding speed versus contact area from incremental slicing depths showed that a larger asperity contact surface pointed to faster sliding, but an increase in the polished surface area reduced sliding. As such, analysis of the surface at different length scales has revealed different design elements—asperities, grooves, curved zones—to alter the sliding speed on ice.

A Holistic Approach Towards Surface Topography Analyses for Ice Tribology Applications

A surface texture can be subdivided into three categories based on the magnitude of its wavelengths, i.e., macro-geometrical form, waviness, and roughness (from largest to smallest). Together, these components define how a surface will interact with the opposing surface. In most ice tribology studies, <2% of the entire sample surface is topographically analyzed. Although such a small percentage of the entire surface area generally provides statistically relevant information, the missing information about the texture complexity on a larger scale might reduce the possibility of accurately explaining the resulting tribological behavior. The purpose of this study was to review the existing surface measurement methods related to ice tribology and to present a holistic approach towards surface topography measurements for ice tribology applications. With the holistic surface measurement approach, the entire sample surfaces are scanned, and the measured data is analyzed on different magnitude levels. The discussed approach was applied to sandblasted steel samples which were afterward tested on two different ice tribometers. The experimental results showed that additional information about the sample surface topography enabled a better understanding of the ice friction mechanisms and allowed for a more straightforward correlation between the sample surface topography and its ice friction response.

Comment on “Improved pivot-slide model of the motion of a curling rock”

We point out three errors in a recent paper that is based on one of our two papers. Together our two papers describe a first-principles “pivot-slide model” of the motion of a curling rock. The most serious error is that the “improved pivot-slide model” (Mancini and de Schoulepnikoff. Can. J. Phys. 97(12), 1301 (2019) doi: 10.1139/cjp-2018-0356 ) is based on only our first paper, whereas the most important work in our model was described in our second paper, which those authors have overlooked. Another error is that the authors claim we use constant friction, whereas we actually use a velocity-dependent formulation of the ice friction coefficient. Thirdly, the authors use a time-dependent function for the ratio of pivoting time to sliding time, whereas in our second paper, we showed from first principles that this ratio does not depend on time.