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Research Papers: Gas Turbines: Microturbines and Small Turbomachinery

Evolutionary Optimization of Micro-Thrust Bearings With Periodic Partial Trapezoidal Surface Texturing

[+] Author and Article Information
Christos I. Papadopoulos

School of Naval Architecture and Marine Engineering, National Technical University of Athens, 9 Heroon Polytechniou Street, 15710 Zografos, Greecechpap@central.ntua.gr

Pantelis G. Nikolakopoulos

Machine Design Laboratory, Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, Greecepnikolak@mech.upatras.gr

Lambros Kaiktsis

School of Naval Architecture and Marine Engineering, National Technical University of Athens, 9 Heroon Polytechniou Street, 15710 Zografos, Greecekaiktsis@naval.ntua.gr

J. Eng. Gas Turbines Power 133(1), 012301 (Sep 27, 2010) (10 pages) doi:10.1115/1.4001990 History: Received April 12, 2010; Revised April 26, 2010; Published September 27, 2010; Online September 27, 2010

An optimization study of trapezoidal surface texturing in slider micro-bearings, via computational fluid dynamics (CFD), is presented. The bearings are modeled as micro-channels, consisting of a moving and a stationary wall. The moving wall (rotor) is assumed smooth, while part of the stationary wall (stator) exhibits periodic dimples of trapezoidal form. The extent of the textured part of the stator and the dimple geometry are defined parametrically; thus, a wide range of texturing configurations is considered. Flow simulations are based on the numerical solution of the Navier–Stokes equations for incompressible isothermal flow. To optimize the bearing performance, an optimization problem is formulated and solved by coupling the CFD code with an optimization tool based on genetic algorithms and local search methods. Here, the design variables define the bearing geometry, while load carrying capacity is the objective function to be maximized. Optimized texturing geometries are obtained for the case of parallel bearings for several numbers of dimples, illustrating significant load carrying capacity levels. Further, these optimized texturing patterns are applied to converging bearings for different convergence ratio values; the results demonstrate that, for small and moderate convergence ratios, a substantial increase in load carrying capacity, in comparison to smooth bearings, is obtained. Finally, an optimization study performed at a high convergence ratio shows that, in comparison to the parallel slider, the optimal texturing geometry is substantially different, and that performance improvement over smooth bearings is possible even for steep sliders.

Copyright © 2011 by American Society of Mechanical Engineers
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Figures

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Figure 1

(a) Two-dimensional textured slider geometry (parallel slider for H1=H0), (b) trapezoidal geometry of dimples, and (c) typical thrust bearing application with partial texturing

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Figure 2

Detail of typical mesh at the inlet of a parallel slider

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Figure 3

Computed nondimensional pressure distribution versus nondimensional streamwise coordinate for a converging micro-bearing with texturing: present work and results in Ref. 5

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Figure 5

Schematics of crossover and mutation operations

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Figure 6

Optimal parallel micro-bearing geometries for various dimple numbers (domain is scaled by 1/2 in the x direction)

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Figure 7

Parallel textured bearing: (a) Optimal load carrying capacity and corresponding friction coefficient versus number of dimples. (b) Nondimensional pressure distribution on the moving wall for the optimal micro-bearings of Fig. 6 and for the optimal step bearing.

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Figure 8

Optimal parallel bearing with N=3: variation in load carrying capacity versus the design variables in the regime of the optimum

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Figure 9

Case with N=3: backflow (negative streamwise velocity) regions for different values of relative dimple height, s (domain is scaled by 1/2 in the x direction)

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Figure 10

Case with N=3. ((a)–(c)) Profiles of the nondimensional streamwise velocity at a cross section in the center of the first dimple for different values of relative dimple height, s. (d) Corresponding distributions of nondimensional pressure on the moving wall of the bearing.

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Figure 11

Case with N=3: backflow (negative streamwise velocity) regions for different values of nondimensional untextured outlet length, luo (domain is scaled by 1/2 in the x direction)

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Figure 12

Case with N=3. ((a)–(c)) Profiles of the nondimensional streamwise velocity at a cross section in the center of the first dimple for different values of nondimensional untextured outlet length, luo. (d) Corresponding distributions of nondimensional pressure on the moving wall of the bearing.

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Figure 13

Case with N=3: backflow (negative streamwise velocity) regions for inclined and vertical trapezoid legs (domain is scaled by 1/2 in the x direction)

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Figure 14

(a) Load carrying capacity and (b) friction coefficient versus convergence ratio, k, for smooth and textured bearings. The corresponding relative differences are also included. Texturing utilizes the optimal pattern obtained for parallel bearings with dimple number N=3.

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Figure 15

Optimal geometry of a converging bearing with k=1.2 (domain is scaled by 1/2 in the x direction)

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