Browse Publications Technical Papers 2011-01-1049
2011-04-12

A Comparative Study of Bearing Press Fit Contact Modeling Techniques with Current Finite Element Analysis Tools 2011-01-1049

Bearing press fits have a wide range of application in ground vehicles and are typically governed by longstanding rules of thumb for designs that conform to past successful design geometries and practice. However, in unusual applications such as a gear box designed to also bear external loads, the combined stress states require finite element analysis (FEA) that accounts for the press fit, the bearing loads due to torque transmission, and the external loading. Therefore accurate prediction of press fit stress states are required to construct complete solutions to gear box fatigue life prediction and in particular to predict mean stress states.
Current FEA tools provide a variety of analysis methods with which to approach the problem of press fit mechanics. Using a notional load bearing gear box with a bearing press fit, several approaches to the stress state prediction are compared and contrasted, ranging from procedures implemented in a linear solver to the use of general contact algorithms implemented in an explicit FEA solver. The study is bounded by the desire to take advantage of automated FEA mesh generation capabilities and therefore focuses on the relative merits of the tetrahedral finite elements formulation derived for use in press fit and contact algorithms. A baseline reference solution for the independent press fit problem is posed from the analytical solution for thick-walled cylinders subject to symmetric external loading. Various options available in FEA solvers are then compared for this class of problem and to the well known pseudo-thermal load models.
As each code exhibits sensitivity to element size and order and offers a range of algorithm tuning parameters, the impact of each are discussed theoretically and explored numerically where application directly affects design practice or requires a numerical simulation assumption that creates uncertainty in the results.

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