In conventional rotordynamic modeling, hydrodynamic bearings are often characterized by a set of linear stiffness and damping coefficients obtained from a first-order Taylor series expansion of bearing reactions. Theoretically. these coefficients are only valid for small amplitude motion about an equilibrium position. In this paper, a nonlinear dynamic model that overcomes the small amplitude assumption in the conventional linear analysis is described, By including higher-order terms in the bearing reaction expansion, nonlinearity in the oil film forces for large amplitude motion can be captured and represented by a set of nonlinear stiffness and damping coefficients. These coefficients are functions of static bearing displacement. A finite difference approach is described and is used to solve for these coefficients. The stated model is applied to a conventional slider bearing and a mechanical smart slider bearing that experiences large variations in load. Error assessment is performed numerically on the higher-order solutions to determine an acceptable displacement bound for the higher order coefficients.

/pdf/a-nonlinear-dynamic-model-with-confidence-bounds-for-nyamboatnt.pdf

A Nonlinear Dynamic Model With Confidence Bounds for Hydrodynamic Bearings

Self Adapting Mechanical Step Bearings for Variations in Load

Fluid-structure interactions in hydrodynamic bearings result in load carrying and drag forces which give the bearing its characteristics. While these bearings offer many benefits as machine components, one of their shortcomings is their limited efficient range. In this paper, we demonstrate the use of micron-scale actuators to actively control the thrust and drag forces on a slider bearing. We show that for a set of control parameters, we are able to affect the performance of a bearing by more than 100 percent during operation, increasing the bearing's range of operation.

/pdf/induced-micro-variations-in-hydrodynamic-bearings-1reb0tjzsd.pdf

Induced Micro-Variations in Hydrodynamic Bearings

Novel Self-Adapting Microscale Surface Textures For Hydrodynamic Lubrication

Fluid-Structure interactions in hydrodynamic bearings result in load carrying and drag forces which give the bearing its characteristics. While these bearings offer many benefits as machine components, one of their shortcomings is their limited efficient range. In this paper, we demonstrate the use of micron-scale actuators to actively control the lift and drag forces on a slider bearing. We show that for a set of control parameters, we are able to affect the performance of a bearing by more than 100% during operation, increasing the bearing’s range of operation.

/pdf/smart-hydrodynamic-bearings-using-surface-micro-variations-513x8i3yc1.pdf

Smart hydrodynamic bearings using surface micro variations

: Microdynamical systems have been studied for a number of years. Only limited work, however, has been completed on integrating microdynamical components into systems that satisfy mechanical tasks on macroscopic scales. In this paper, we describe microdynamical components that are needed to produce a surface which is actively deformable on local scales. In particular, we consider the design and demonstration of smart journal and thrust bearings capable of using embedded sensors and actuators to dynamically change the surface geometry. The ability to actively deform bearing surfaces allows for the design of bearings which are less prone to failure, the design of bearings with greater load carrying abilities, and a fundamental study of the effect of surface geometries and fluid conditions on bearing performance, such as start-up and shut-down conditions. Results of our new bearing designs are presented, focusing on numerical bearing models, sensor and actuator design and fabrication, and physical experimentation.

MEMS Hydrodynamic Bearings: Applications and Implications to Machine-Failure Prevention

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MEMS Hydrodynamic Bearings: Applications and Implications to Machine-Failure Prevention