DOI: 10.5061/dryad.ttdz08m4v
title: Data from: Spectral wear modelling of rubber friction on a hard substrate with large surface roughness

description: 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.
description: # Data from: Spectral wear modelling of rubber friction on a hard
 substrate with large surface roughness
 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