Data from: Spectral wear modelling of rubber friction on a hard substrate with large surface roughness
Data files
Dec 17, 2023 version files 3 GB
-
Appendix.zip
-
README.md
-
Section2.zip
-
Section3.zip
-
Section4.zip
-
Section5.zip
Abstract
Soft-hard matter friction is a long-standing tribology problem that remains unclarified, requiring engineers to empirically predict the wear life. To clarify this issue, this study examines the transient running-in regime of rubber friction on a hard rough substrate and models the temporal wear progression using the spectrum curves of surface roughness for both materials. Performing a series of friction tests and three-dimensional surface-height measurements, the time-dependent behaviours of the power spectral densities (PSDs) are divided into two phases, namely the initial non-steady and long-term steady phases. The detailed spectral analyses of worn rubber surfaces in the initial phase lead to a blended PSD function between self-affine and K-correlation surface models, consisting of one variable (the Hurst exponent) that is saturated by the substrate self-affinity. Supported by the Greenwood–Williamson theory concerning rough contact mechanics, the volumetric estimate with the blended PSD function is used to assess the volume rate of wear debris in the steady phase, which is validated experimentally. These findings not only improve the wear predictions of soft materials from previous measurements of worn surfaces but also help clarify the constrained multiscale mechanism of wear.
README: Data from: Spectral wear modelling of rubber friction on a hard substrate with large surface roughness
https://doi.org/10.5061/dryad.ttdz08m4v
Structure:
Section2.zip
|- 2_1/
| |- fig/
|- 2_2/
|- 2_3/
| |- Python/
| | |- fig/
| |- Rubber2/
| |- Rubber11/
| |- Rubber16/
| |- Rubber17/
| |- Rubber20/
| |- Rubber21/
Section3.zip
|- 3_2/
| |- PSDcalc/
|- 3_3/
| |- fig_matlab/
| |- PSDcalc/
|- 3_4/
| |- fig_matlab/
Section4.zip
|- 4_1/
| |- fig_matlab/
Section5.zip
|- 5_2/
| |-fig_matlab/
Appendix.zip
|- A/
| |- Grindstone_surfaces/
| | |- All_images_grindstone_40x
| | |- All_images_grindstone_400x
| |- Worn_rubber_surfaces/
| | |- All_images_Rubber21_12x
| | |- All_images_Rubber21_40x
| | |- All_images_Rubber21_400x
|- D/
Abbreviations:
Power Spectral Density (PSD)
Coefficient of Friction (COF)
Usage notes:
(1) These datasets include the experimental and numerical data (excel or csv files), the source codes of the MATLAB and Python programs, and the generated figure files. The file structure corresponds to the related journal-article composition. There are the local documents of "README.txt", which explain the individual data files and the local file structures, specifically prepared in the sub-sectional directories.
(2) In data, the rubber block samples are numbered for the sake of an experimental procedure, while they are labelled as Rubbers A-F in the manuscript. The correspondence relation is shown below.
Rubber A = Rubber #2
Rubber B = Rubber #11
Rubber C = Rubber #16
Rubber D = Rubber #17
Rubber E = Rubber #20
Rubber F = Rubber #21
(3) Basically, the MATLAB programs are written in SI units (N,m) but, only in the program codes of Section 4, we employ a (N,mm,MPa)-system to solve the contact problems.
(4) The operated versions are listed as follows.
MATLAB version: 9.13 (R2022b)
Curve Fitting Toolbox version: 3.8 (R2022b)
Statistics and Machine Learning Toolbox version: 12.4 (R2022b)
Python version: 3.11.3
Jupyter-notebook version: 6.5.4
Prepared by: Hiro Tanaka