Abstract
The Morton effect (ME) occurs when a bearing journal experiences asymmetric heating due to synchronous vibration, resulting in thermal bowing of the shaft and increasing vibration. An accurate prediction of the journal's asymmetric temperature distribution is critical for reliable ME simulation. This distribution is strongly influenced by the film thermal boundary condition at the pad inlets. Part I utilizes machine learning (ML) to obtain a two-dimensional radial and axial distribution of temperatures over the leading-edge film cross section. The hybrid finite volume method (FVM)—bulk flow method of Part I eliminated film temperature discontinuities and is utilized in Part II for improving accuracy and efficiency of ME simulation.
Issue Section:
Hydrodynamic Lubrication
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