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February 11, 2026Physics of Fluids3 citations

Mixed elastohydrodynamic lubrication analysis of roller-race contacts in tunnel boring machine main bearings

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YPYongdong PengCFCongcong FangWZWei Zhou

Key Points

  • The study aims to develop a comprehensive lubrication model to enhance the performance of main bearings in tunnel boring machines.
  • Developed a coupled mixed elastohydrodynamic lubrication-friction model
  • Utilized a parallel finite-element strategy to improve computational efficiency
  • Validated model against experimental data for roller-race contacts
  • Incorporated both boundary and viscous friction components
  • The logarithmic roller profile significantly improves lubrication performance
  • Under high-load conditions, increased viscosity slightly reduces axial friction force
  • A high-viscosity lubricant (Grade 680) decreases total friction torque by 4.26%
  • Overall frictional power loss is reduced by 4.24%, indicating efficiency improvements

Abstract

The main bearing is essential for ensuring the service life and functional reliability of tunnel boring machines. This work develops a fully coupled mixed elastohydrodynamic lubrication-friction model, accelerated via a parallel finite-element strategy that improves computational efficiency by up to 90%, and validated against experimental roller-race contact data. The model incorporates contact analyses across bearing rows and accounts for both boundary and viscous friction components to comprehensively assess friction force and torque. Results indicate that the logarithmic roller profile enhances lubrication performance. Notably, under high-load conditions where lubricant shear stress reaches its limit, increasing viscosity leads to a slight reduction in axial friction force. Employing a high-viscosity lubricant (Viscosity Grade 680) reduces total friction torque by 4.26%, along with a 4.24% decrease in overall frictional power loss, indicating meaningful efficiency improvements.

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Cite This Study

Peng et al. (2026) studied this question.

synapsesocial.com/papers/698c1cc1267fb587c655f7d3https://doi.org/10.1063/5.0308178
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