README File for Dataset in support of the thesis titled 'Study and modelling of surface topography changes during running-in in rolling-sliding contacts under mixed lubrication'

Dataset DOI: https://doi.org/10.5258/SOTON/D3251

ReadMe Author: Maruti Sai Dhiraj Sakhamuri, University of Southampton ORCID ID: 0000-0001-7607-3087

This dataset supports the thesis entitled: Study and Modelling of Surface Topography Changes During Running-in in Rolling-Sliding Contacts Under Mixed Lubrication

AWARDED BY: University of Southampton

DATE OF AWARD: 2024

DESCRIPTION OF THE DATA:
This dataset contains the data generated during the PhD research titled ?Study and Modelling of Surface Topography Changes During Running-in in Rolling-Sliding Contacts Under Mixed Lubrication.? The testing involved two tribometers: TE74 and MTM. The data is organised into five primary folders based on the type of tribometer and the nature of the data acquisition (online vs. offline).
Folder Structure
* TE74 Online Data: Online data generated during the TE74 tribometer testing.
o Each subfolder is labelled by the corresponding test number.
o For detailed information about each test (e.g., parameters, materials, conditions), refer to the thesis document.
* TE74 Offline Data: Offline data for tests conducted using the TE74 tribometer.
o Includes axial 2D profilometry scans of the discs.
o Subfolders are organised by test number, with test details available in the thesis.
* MTM Online Data: Online data from the MTM tribometer testing.
o Subfolders named according to the respective test number.
o Test details (parameters, materials, and testing conditions) are described in the thesis.
* MTM Offline Data Part 1 and MTM Offline Data Part 2: Offline data for tests conducted with the MTM tribometer.
o Consists of SEM (Scanning Electron Microscopy) images and 3D profilometry scans of the wear surface.
o Subfolders are organised by test number, with detailed descriptions in the thesis.

Date of data collection: 2019-2023

Information about geographic location of data collection: nCATS lab, University of Southampton, Southampton, United Kingdom

Licence:
CC BY

Related projects/Funders:
Early detection of contact distress for Enhanced performance monitoring and predictive inspection of machines

Related publication:
Sakhamuri, M.S.D., Harvey, T.J., Vierneusel, B. and Wood, R.J., 2023. Wear induced changes in surface topography during running-in of rolling-sliding contacts.˙Wear,˙522, p.204685.
https://doi.org/10.1016/j.wear.2023.204685

Date that the file was created: September 2024