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This paper presents the first simulation model of a tilting pad journal bearing (TPJB) using three-dimensional (3D) computational fluid dynamics (CFD), including multiphase flow, thermal-fluid, transitional turbulence, and thermal deformation of the shaft and pads employing two-way fluid–structure interaction (FSI). Part I presents a modeling method for the static performance. The model includes flow between pads BP, which eliminates the use of an uncertain, mixing coefficient (MC) in Reynold's equation approaches. The CFD model is benchmarked with Reynold's model with a 3D thermal-film, when the CFD model boundary conditions are consistent with the Reynolds boundary conditions. The Reynolds model employs an oversimplified MC representation of the three-dimensional mixing effect of the BP flow and heat transfer, and it also employs simplifying assumptions for the flow and heat transfer within the thin film between the journal and bearing. This manufactured comparison shows good agreement between the CFD and Reynold's equation models. The CFD model is generalized by removing these fictitious boundary conditions on pad inlets and outlets and instead models the flow and temperature between pads. The results show that Reynold's model MC approach can lead to significant differences with the CFD model including detailed flow and thermal modeling between pads. Thus, the CFD approach provides increased reliability of predictions. The paper provides an instructive methodology including detailed steps for properly applying CFD to tilt pad bearing modeling. Parts I and II focus on predicting static and dynamic response characteristic responses, respectively.

Traditional analysis of journal bearings assumed a constant viscosity which simplified the solutions for static and dynamic characteristics and responses. Today's high-performance machinery requires more accurate models wherein temperature and viscosity distributions in the film must be calculated. Thermal effects in journal bearings have a strong influence on both static and dynamic properties, and consequently play a critical role in determining rotor-bearing system performance. This paper presents an extensive survey of the thermal modeling methods and effects in journal bearings. The subjects include various bearing types, and recent progress in thermal bearing design and thermal instability problems observed in fluid and gas film hydrodynamic bearings. The extent of the survey ranges from conventional Reynolds equation models to more advanced CFD models.

Part II presents a novel approach for predicting dynamic coefficients for a tilting pad journal bearing (TPJB) using computational fluid dynamics (CFD) and finite element method (FEM), including fully coupled elastic deflection, heat transfer, and fluid dynamics. Part I presented a similarly novel, high fidelity approach for TPJB static response prediction which is a prerequisite for the dynamic characteristic determination. The static response establishes the equilibrium operating point values for eccentricity, attitude angle, deflections, temperatures, pressures, etc. The stiffness and damping coefficients are obtained by perturbing the pad and journal motions about this operating point to determine changes in forces and moments. The stiffness and damping coefficients are presented in “synchronously reduced form” as required by American Petroleum Institute (API) vibration standards. Similar to Part I, an advanced three-dimensional thermal—Reynolds equation code validates the CFD code for the special case when flow Between Pad (BP) regions is ignored, and the CFD and Reynolds pad boundary conditions are made identical. The results show excellent agreement for this validation case. Similar to the static response case, the dynamic characteristics from the Reynolds model show large discrepancies compared with the CFD results, depending on the Reynolds mixing coefficient (MC). The discrepancies are a concern given the key role that stiffness and damping coefficients serve instability and response predictions in rotordynamics software. The uncertainty of the MC and its significant influence on static and dynamic response predictions emphasizes a need to utilize the CFD approach for TPJB simulation in critical machines.