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Influence of Surface Roughness Effects on the Lubrication Performance of External Gear Machines

[+] Author Affiliations
Divya Thiagarajan, Andrea Bratto, Andrea Vacca

Purdue University, Lafayette, IN

Paper No. FPMC2017-4309, pp. V001T01A054; 10 pages
  • ASME/BATH 2017 Symposium on Fluid Power and Motion Control
  • ASME/BATH 2017 Symposium on Fluid Power and Motion Control
  • Sarasota, Forida, USA, October 16–19, 2017
  • Conference Sponsors: Fluid Power Systems and Technology Division
  • ISBN: 978-0-7918-5833-2
  • Copyright © 2017 by ASME


In pressure compensated external gear machines (EGMs), lateral lubricating interfaces exist between floating lateral bushings and gears. These interfaces are primarily responsible for supporting the high pressure bearing loads in these gaps and promoting good operating efficiencies of these units. A fully coupled fluid-structure-thermal interaction lateral gap model has been developed previously in the authors’ research team which considers this highly coupled physical phenomena to predict the lubrication performance of the interface under full film as well as mixed film conditions. In the current work, capabilities of the lateral gap model are utilized in studying the impact of the variations in surface finishes on the performance of a commercially available EGM chosen for this study.

Lateral plate designs of varying surface roughness are chosen for the same EGM unit, to analyze their influence on the lubricating performance of the unit. Detailed surface profile measurements were carried out on these lateral plates under study to determine precise inputs to the lateral gap model. Resulting numerical simulations from the gap model over different operating conditions are used to examine the significant performance features associated with the lateral interface which are affected by such surface variations. Furthermore, the paper compares the simulated leakages obtained directly from the lateral gap model for each of the lateral plate designs, with corresponding experimental data over a wide range of operating conditions.

Copyright © 2017 by ASME



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