Modelling self-healing magnetic textures in hydrodynamic bearings

Modelling self-healing magnetic textures in hydrodynamic bearings

van der Meer, Gerben (TU Delft Mechanical, Maritime and Materials Engineering; TU Delft Precision and Microsystems Engineering)

van Ostayen, R.A.J. (mentor)

Delft University of Technology

Mechanical Engineering | Mechatronic System Design (MSD)

2020-12-15

Hydrodynamic bearings can be used to minimise friction, and their load capacity can be improved by texturing the bearing surfaces. However, due to mechanical contact between the surfaces during start and stop, these textures are susceptible to wear. Previously, a new method of creating textures using magnetorheological fluids as lubricant was discovered. By locally applying strongly non-uniform magnetic fields to the bearing, the magnetic particles contained in the fluid can be pulled towards the bearing surfaces. The resulting texture-like accumulation of particles on these surfaces improves load capacity, and has been shown experimentally to be self-healing. However, theoretically not much is known about these textures. This thesis presents a numerical model based on the Reynolds equation and the concept of critical shear stress that can determine the steady-state behaviour of these self-healing textures, as well as their effect on bearing performance. The model has been compared with existing experiments, showing qualitative agreement.

self-healing
hydrodynamic bearing
surface texture
magnetorheological fluid
critical shear stress

http://resolver.tudelft.nl/uuid:4101c67a-71ef-4be2-b6bd-8abfaf84290b

2022-12-15

Student theses

master thesis

© 2020 Gerben van der Meer