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Outputs (13)

A machine learning-driven approach to predicting thermo-elasto-hydrodynamic lubrication in journal bearings (2024)
Journal Article

Traditional methods of evaluating the performance of journal bearings, for example thermal-elastic-hydrodynamic- lubrication theory, are limited to simplified conditions that often fail to accurately model real-world components. Numerical models that... Read More about A machine learning-driven approach to predicting thermo-elasto-hydrodynamic lubrication in journal bearings.

Towards a more reliable interpretation of machine learning outputs for safety-critical systems using feature importance fusion (2021)
Journal Article

When machine learning supports decision-making in safety-critical systems, it is important to verify and understand the reasons why a particular output is produced. Although feature importance calculation approaches assist in interpretation, there is... Read More about Towards a more reliable interpretation of machine learning outputs for safety-critical systems using feature importance fusion.

Analysis of the tribological interaction of a polytetrafluoroethylene-lined radial lip oil seal, shaft and lubricant sample (2021)
Journal Article

To investigate the tribological interaction and wear mechanisms of polytetrafluoroethylene-lined radial lip oil seals in service, a sleeve, seal and lubricant sample taken off a rotating rig are studied. The test was terminated at 72 h, after severe... Read More about Analysis of the tribological interaction of a polytetrafluoroethylene-lined radial lip oil seal, shaft and lubricant sample.