Research Papers: Gas Turbines: Structures and Dynamics

Effect of Foil Geometry on the Static Performance of Thrust Foil Bearings

[+] Author and Article Information
Gen Fu

Laboratory for Turbomachinery
and Components,
Department of Biomedical Engineering
and Mechanics,
Virginia Tech,
Norris Hall, Room 107,
Virginia Tech 495 Old Turner Street,
Blacksburg, VA 24061
e-mail: gen8@vt.edu

Alexandrina Untaroiu

Laboratory for Turbomachinery and
Department of Biomedical
Engineering and Mechanics,
Virginia Tech,
Norris Hall, Room 107,
Virginia Tech 495 Old Turner Street,
Blacksburg, VA 24061
e-mail: alexu@vt.edu

Erik Swanson

Xdot Engineering and Analysis,
Charlottesville, VA 22901
e-mail: Erik@XdotEA.com

1Corresponding author.

Contributed by the Structures and Dynamics Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received August 28, 2017; final manuscript received October 4, 2017; published online April 12, 2018. Editor: David Wisler.

J. Eng. Gas Turbines Power 140(8), 082502 (Apr 12, 2018) (9 pages) Paper No: GTP-17-1482; doi: 10.1115/1.4038693 History: Received August 28, 2017; Revised October 04, 2017

Gas foil bearings can operate in extreme conditions such as high temperature and high rotating speed, compared to traditional bearings. They also provide better damping and stability characteristics and have larger tolerance to debris and rotor misalignment. Gas foil bearings have been successfully applied to micro- and small-sized turbomachinery, such as microgas turbine and cryogenic turbo expander. In the last decades, a lot of theoretical and experimental work has been conducted to investigate the properties of gas foil bearings. However, very little work has been done to study the influence of the foil bearing pad configuration. This study proposes a robust approach to analyze the effect of the foil geometry on the performance of a six-pad thrust foil bearing. In this study, a three-dimensional (3D) computational fluid dynamics (CFD) model for a parallel six-pad thrust foil bearing is created. In order to predict the thermal property, the total energy with viscous dissipation is used. Based on this model, the geometry of the thrust foil bearing is parameterized and analyzed using the design of experiments (DOE) methodology. In this paper, the selected geometry parameters of the foil structure include minimum film thickness, inlet film thickness, the ramp extent on the inner circle, the ramp extent on the outer circle, the arc extent of the pad, and the orientation of the leading edge. The objectives in the sensitivity study are load capacity and maximal temperature. An optimal foil geometry is derived based on the results of the DOE process by using a goal-driven optimization technique to maximize the load capacity and minimize the maximal temperature. The results show that the geometry of the foil structure is a key factor for foil bearing performance. The numerical approach proposed in this study is expected to be useful from the thrust foil bearing design perspective.

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Fig. 1

Configuration of the foil thrust bearing: (a) thrust foil bearing and (b) working principle of thrust foil bearing

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Fig. 2

Boundary conditions for baseline model

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Fig. 3

Load capacity versus mesh density

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Fig. 4

Final mesh of the baseline model

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Fig. 5

Load capacity versus operating speed

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Fig. 6

Drag torque versus load capacity

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Fig. 7

Parameterization of the geometry

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Fig. 8

Pressure distribution of baseline model

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Fig. 9

Temperature distribution of baseline model

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Fig. 10

Good of fitness: (a) load capacity and (b) maximum temperature

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Fig. 11

Response surface plots: (a) load capacity versus θo and θi, (b) load capacity versus θ and α, (c) load capacity versus h and t, (d) maximal temperature versus θo and θi, (e) maximal temperature versus θ and α, and (f) maximal temperature versus h and t

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Fig. 12

Local sensitivity for load capacity and maximal temperature, (a) load capacity and (b) maximum temperature

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Fig. 14

Pressure distribution from the first optimal design

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Fig. 15

Temperature distribution from the second optimal design



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