Surrogate Model Based Optimization for Chevron Foil Thrust Bearing

Abstract

Gas foil thrust bearings have been utilized in high speed lightweight machines for many decades. These bearings are environment-friendly and capable of withstanding extreme conditions. However, there are also some challenges for foil thrust bearings at high speed conditions, such as insufficient heat dissipation and thermal management. The heat generated by viscous shearing continues to raise the temperature inside the gas film and may cause failures. Among all the methods to enhance heat dissipation, a promising passive thermal management method is modifying the top foil’s trailing edge shape. This modification will enhance the air mixing in between the bearing pads. The aim of this study is to identify the optimal design of the top foil trailing edge shape and provide a guideline for future bearing design. A 3-D computational fluid dynamics (CFD) model for a thrust foil bearing was created using ANSYS-CFX software. The trailing edge of the top foil was modified to a chevron shape. A sensitivity study was conducted to investigate the connection between the top foil trailing edge shape and the thermal conditions in the gas film. The maximum temperature inside the air gas film is selected as the output. The design of experiments (DOE) technique was used to generate the sampling points. A surrogate model was generated based on the output data by using the neural network method. The surrogate model was used together with a genetic multi-objective algorithm to minimize the maximal temperature inside the gas film and maximize the load carrying capacity. The optimal design was then compared with the baseline model. Results suggest the optimized trailing edge shape is capable of reducing the temperature inside the gas film. This optimal design approach can be used for improvements of chevron foil thrust bearing design.