2001Industrial Lubrication and TribologyRequires access

Non‐linear solution of Reynolds equation for thermo‐elastohydrodynamic analysis of thrust pad bearing

Ankita Sinha, K. Athre, Somjeet Biswas

Open publisher page 4 citations

Abstract

The treatment of Reynolds equation when the film thickness is unknown and the center of pressure is known, together with the energy and the bending equation, allows a realistic simulation of the performance of large thrust bearing. In a spring‐supported thrust‐pad bearing the distortion caused by the generated pressure thermal gradient yields a surface profile of opposite shapes. The thermoelastic analysis performed here makes it possible to determine the resultant film shape of the thrust pad.

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What this paper is about

The treatment of Reynolds equation when the film thickness is unknown and the center of pressure is known, together with the energy and the bending equation, allows a realistic simulation of the performance of large thrust bearing. In a spring‐supported thrust‐pad bearing the distortion caused by the generated pressure thermal gradient yields a surface profile of opposite shapes. The thermoelastic analysis performed here makes it possible to determine the resultant film shape of the thrust pad.

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Available abstract

The treatment of Reynolds equation when the film thickness is unknown and the center of pressure is known, together with the energy and the bending equation, allows a realistic simulation of the performance of large thrust bearing. In a spring‐supported thrust‐pad bearing the distortion caused by the generated pressure thermal gradient yields a surface profile of opposite shapes. The thermoelastic analysis performed here makes it possible to determine the resultant film shape of the thrust pad.

Key concepts: Thrust bearing, Reynolds equation, Thrust, Bearing (navigation), Mechanics, Thermoelastic damping, Materials science, Bending

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Non‐linear solution of Reynolds equation for thermo‐elastohydrodynamic analysis of thrust pad bearing — Research Paper | ScholarLens