Editorial Type:
Article Category: Research Article
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Online Publication Date: 09 Jun 2025

Frictional Abrasion of Rubber: Transition from Sliding to Rolling

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Page Range: 134 – 161
DOI: 10.2346/TST-24-004
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ABSTRACT

To develop applicable friction and wear models on tire scale, reliable test data are required. Consequently, friction tests on block level are requested because the distribution of contact pressure as well as slip velocity is nearly homogeneous at the contact surface of the sliding rubber block. However, wear mechanism and energy intensity levels of sliding rubber blocks and rolling rubber wheels or tires differ significantly. Consequently, linking both sliding and rolling frictional abrasion is required; thus, a wear model for rubber material is introduced to consider both deformation slip and sliding. The model input for sliding friction and resulting wear rate is derived from linear friction test experiments using sliding rubber blocks at different loading. A unique and sophisticated re-mesh algorithm ensures proper mesh modification due to abrasion of the structure. A wear energy evolution approach is developed to consider low abrasion with small sliding distances to predict wear at rolling rubber wheels. The simulation framework of abrasion modeling is successfully validated using laboratory abrasion tests.

Keywords: frictional abrasion; linear friction tester; laboratory abrasion tester; modeling wear; re-mesh algorithm; FEM
FIG. 1
FIG. 1

Linear friction and LAT.

FIG. 2
FIG. 2

Abrasion residue on sandpaper grit 60 and on LAT disc grit 60.

FIG. 3
FIG. 3

Measured friction coefficient and mass wear rate during LFT abrasion tests.

FIG. 4
FIG. 4

Deviation of recorded friction and wear during LFT experiment using sandpaper grit 60 and LAT disc grit 60.

FIG. 5
FIG. 5

Measured side force and mass loss rate during LAT protocol.

FIG. 6
FIG. 6

Grosch wheel segment at height of 40 mm.

FIG. 7
FIG. 7

Identification of Huemer friction model parameters by fitting Eq. (10) to LFT measurements.

FIG. 8
FIG. 8

Identification of wear model parameters.

FIG. 9
FIG. 9

Wear energy rate evolution function.

FIG. 10
FIG. 10

Re-meshing of FE rubber sample.

FIG. 11
FIG. 11

Simulation framework of abrasion modeling.

FIG. 12
FIG. 12

FE model of sliding Grosch wheel segment.

FIG. 13
FIG. 13

Validation of wear rate using LFT at small driving distances.

FIG. 14
FIG. 14

FE model of LAT100.

FIG. 15
FIG. 15

Contact pressure distribution of LAT100 conditions selected from Table 3.

FIG. 16
FIG. 16

Sliding velocity distribution of LAT100 conditions selected from Table 3.

FIG. 17
FIG. 17

Distribution of friction coefficient, frictional power intensity, and evolution function of LAT100 at v=25 km/h and α=16°.

FIG. 18
FIG. 18

Validation of frictional energy rate by using LAT.

FIG. 19
FIG. 19

Validation of wear rate by using LAT.

FIG. 20
FIG. 20

Resulting worn node coordinates of the axis-symmetric cross section by using the LAT protocol including the wear energy evolution approach.

FIG. 21
FIG. 21

Computed vs re-meshed (total) wear volume.

FIG. 22
FIG. 22

Computed vs re-meshed (nodal) wear volume.

FIG. 23
FIG. 23

Number of re-mesh runs per test condition and averaged number of re-mesh iterations per re-mesh run.

Contributor Notes

3Corresponding author. Email: michael.kaliske@tu-dresden.de
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