Journal and thrust bearings with textured surfaces: A review of modelling techniques
Journal and thrust bearings with textured surfaces: A review of modelling techniques
Surface structures have been widely reported to be capable of enhancing the performance of journal and thrust bearings and other applications. Understanding the influence of surface properties (roughness, grooves, textures/dimples) on the performance of hydrodynamically lubricated contacts has thus been the aim of numerous theoretical and experimental studies. A variety of numerical models have been employed by many researchers in order to find optimal texture parameters (shape, size, distribution) to increase load carrying capacity and minimum film thickness and to reduce friction and wear. However, the large number of different modelling techniques and complexity in the patterns makes finding the optimum texture a challenging task and has led to contrary conclusions. Choosing the right models and making the correct assumptions is thus a key first step. Moreover the optimum texture design seems to highly depend on the operating conditions. Hence, successful industrial applications are still limited and further research is needed.
This paper outlines the worldwide research effort on surface texturing over the last 20 years, reports the key findings and, in particular, provides a comparative summary of state of the art modelling techniques. This review is intended to facilitate future research in the field of surface texturing for fluid film bearings and other potential applications in rotating equipment.
About 400 publications on textured/rough surfaces have been reviewed and analysed. The results show that more than half of the studies are purely theoretical, based on different forms of the Reynolds equation, Stokes equations or Navier-Stokes equations. Early models were based on basic forms of the Reynolds equation together with non-mass-conserving cavitation algorithms and neglected changes in viscosity and micro-hydrodynamic effects [1]. The advances in computational power and development of more efficient algorithms have led to more sophisticated models in recent years. More advanced models, for example, apply the full Navier-Stokes equations considering temperature effects [2] or solve modified versions of the Reynolds equation to incorporate mass-conserving cavitation and micro-hydrodynamic effects [3]. A comparative summary of the different modelling techniques for fluid flow, cavitation and micro-hydrodynamic effects commonly used to predict the performance of structured surfaces is given in this paper, including a review of available discretization methods and numerical procedures.
Gropper, Daniel
ae8ff6b6-f64b-4b49-9da0-65b153ec027b
Wang, Ling
c50767b1-7474-4094-9b06-4fe64e9fe362
Harvey, Terence
3b94322b-18da-4de8-b1af-56d202677e04
8 October 2015
Gropper, Daniel
ae8ff6b6-f64b-4b49-9da0-65b153ec027b
Wang, Ling
c50767b1-7474-4094-9b06-4fe64e9fe362
Harvey, Terence
3b94322b-18da-4de8-b1af-56d202677e04
Gropper, Daniel, Wang, Ling and Harvey, Terence
(2015)
Journal and thrust bearings with textured surfaces: A review of modelling techniques.
14th EDF/Pprime Workshop, Poitiers, France.
07 - 08 Oct 2015.
Record type:
Conference or Workshop Item
(Paper)
Abstract
Surface structures have been widely reported to be capable of enhancing the performance of journal and thrust bearings and other applications. Understanding the influence of surface properties (roughness, grooves, textures/dimples) on the performance of hydrodynamically lubricated contacts has thus been the aim of numerous theoretical and experimental studies. A variety of numerical models have been employed by many researchers in order to find optimal texture parameters (shape, size, distribution) to increase load carrying capacity and minimum film thickness and to reduce friction and wear. However, the large number of different modelling techniques and complexity in the patterns makes finding the optimum texture a challenging task and has led to contrary conclusions. Choosing the right models and making the correct assumptions is thus a key first step. Moreover the optimum texture design seems to highly depend on the operating conditions. Hence, successful industrial applications are still limited and further research is needed.
This paper outlines the worldwide research effort on surface texturing over the last 20 years, reports the key findings and, in particular, provides a comparative summary of state of the art modelling techniques. This review is intended to facilitate future research in the field of surface texturing for fluid film bearings and other potential applications in rotating equipment.
About 400 publications on textured/rough surfaces have been reviewed and analysed. The results show that more than half of the studies are purely theoretical, based on different forms of the Reynolds equation, Stokes equations or Navier-Stokes equations. Early models were based on basic forms of the Reynolds equation together with non-mass-conserving cavitation algorithms and neglected changes in viscosity and micro-hydrodynamic effects [1]. The advances in computational power and development of more efficient algorithms have led to more sophisticated models in recent years. More advanced models, for example, apply the full Navier-Stokes equations considering temperature effects [2] or solve modified versions of the Reynolds equation to incorporate mass-conserving cavitation and micro-hydrodynamic effects [3]. A comparative summary of the different modelling techniques for fluid flow, cavitation and micro-hydrodynamic effects commonly used to predict the performance of structured surfaces is given in this paper, including a review of available discretization methods and numerical procedures.
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Published date: 8 October 2015
Venue - Dates:
14th EDF/Pprime Workshop, Poitiers, France, 2015-10-07 - 2015-10-08
Organisations:
nCATS Group, Education Hub
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Local EPrints ID: 410964
URI: http://eprints.soton.ac.uk/id/eprint/410964
PURE UUID: f7ba2be5-3529-41f2-bc17-770e52cba246
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Date deposited: 12 Jun 2017 16:31
Last modified: 12 Dec 2021 03:18
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Author:
Daniel Gropper
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