EngSci-nCATS-304: Surface texturing for hydrodynamic bearings

Surface texturing has recently been explored in optimising tribological performances by controlling friction between two contacting surfaces. While many encouraging results are being obtained, its application in real engineering practices requires a comprehensive understanding of the surface tribology to design, predict and optimise the performance of structured bearings surfaces as well as accommodating cost-effective manufacturing processes.

Supported by John Crane UK Limited, this research aims to investigate the influence of surface texturing on the performance of hydrodynamic bearings through both numerical and experimental studies as well optimising textures in support of future applications in renewable and submerged equipment and low energy hydrodynamic bearings.

Through an EPSRC Case Award from 2014, the current PhD student has developed a mathematic model based on modified Reynolds equations and advanced discretization methods that can prediction performance of textured surfaces accurately but at much faster computing speeds than Computational Fluid Dynamics (CFD). This following on project will continue the significant progress made in the current project but investing wider range of engineering applications for John Crane under varied operating condition, including prediction of dynamic coefficient of damping and stiffness, essential for rotor-dynamic stability of high speed machinery. This research and theoretical work will be supported using the recently developed experimental thrust bearing test rig at John Crane in Slough, UK as well as journal bearing rigs available in Göttingen, Germany, where the PhD student will be working side by side with John Crane bearings experts for 3 Month.

If you wish to discuss any details of the project informally, please contact Dr Ling Wang, nCATS research group, Email: [Email Address Removed] Tel: +44 (0) 2380 59 5076.