This paper is dedicated to the analysis of uncertainties affecting the load capability of a 4-pad tilting-pad journal bearing in which the load is applied on a given pad load on pad configuration (LOP). A well-known stochastic method has been used extensively to model uncertain parameters by using the so-called Monte Carlo simulation. However, in the present contribution, the inherent uncertainties of the bearing parameters (i.e., the pad radius, the oil viscosity, and the radial clearance; bearing assembly clearance) are modeled by using a fuzzy dynamic analysis. This alternative methodology seems to be more appropriate when the stochastic process that characterizes the uncertainties is unknown. The analysis procedure is confined to the load capability of the bearing, being generated by the envelopes of the pressure fields developed on each pad. The hydrodynamic supporting forces are determined by considering a nonlinear model, which is obtained from the solution of the Reynolds equation. The most significant results are associated to the changes in the steady-state condition of the bearing due to the reaction forces that are modified according to the uncertainties introduced in the system. Finally, it is worth mentioning that the uncertainty analysis in this case provides relevant information both for design and maintenance of tilting-pad hydrodynamic bearings.
The modeling of mechanical systems involves different parameters that are susceptible to uncertainties. Commonly, the variations result from the mathematical difficulty of representing the peculiarities of the dynamic systems and the lack of knowledge about the physical properties of the materials used in a given application. In this context, the analysis of uncertainties that affect the performance of the system is an important design issue. Uncertainty analysis of dynamic systems has been studied by applying techniques based on stochastic and fuzzy logic approaches. The fuzzy logic technique seems to be more appropriate when the stochastic process that characterizes the uncertainties is unknown. Therefore, in the present contribution, the inherent uncertainties affecting the performance of a horizontal rotating machine are modeled by using both stochastic and fuzzy logic-based analysis. These methodologies have been compared through numerical simulations in terms of the dynamic behavior of the system as represented by rotor orbits, unbalance responses, and frequency response functions. The proposed uncertainty analysis provides additional information that can be useful for design and maintenance purposes.
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