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Research Papers: Hydrodynamic Lubrication

Discharge Coefficients in Aerostatic Bearings With Inherent Orifice-Type Restrictors

[+] Author and Article Information
S. H. Chang

Department of Mechanical Engineering,
Advanced Institute of Manufacturing With
High-Tech Innovations,
National Chung Cheng University,
Ming-Hsiung, Chiayi County 621, Taiwan
e-mail: shchang314@gmail.com

C. W. Chan

Department of Mechanical Engineering,
Advanced Institute of Manufacturing With
High-Tech Innovations,
National Chung Cheng University,
Ming-Hsiung, Chiayi County 621, Taiwan
e-mail: addison0827@gmail.com

Y. R. Jeng

Department of Mechanical Engineering,
Advanced Institute of Manufacturing With
High-Tech Innovations,
National Chung Cheng University,
Ming-Hsiung, Chiayi County 621, Taiwan
e-mail: imeyrj@ccu.edu.tw

1Corresponding author.

Contributed by the Tribology Division of ASME for publication in the JOURNAL OF TRIBOLOGY. Manuscript received August 4, 2014; final manuscript received September 29, 2014; published online November 6, 2014. Assoc. Editor: George K. Nikas.

J. Tribol 137(1), 011705 (Nov 06, 2014) (7 pages) Paper No: TRIB-14-1194; doi: 10.1115/1.4028737 History: Received August 04, 2014; Revised September 29, 2014

In aerostatic bearing analysis, determining film pressure by solving the Reynolds equation in a numerical model is more effective than conducting bearing experiments or performing computational fluid dynamics (CFD) simulations. However, the discharge coefficient of an orifice-type restrictor is generally a given number that dominates model accuracy. This study investigated the influence of geometry and flow parameters on this discharge coefficient. The results indicate that this discharge coefficient is sensitive to the orifice diameter and film thickness and that the effects of the supply pressure, bearing radius, supply orifice length, supply passage diameter, conicity depth, and conicity angle can be disregarded. This study also built a surrogate model of this discharge coefficient based on the orifice diameter and film thickness by using artificial neural networks (ANNs).

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References

Chen, X. D., and He, X. M., 2006, “The Effect of the Recess Shape on Performance Analysis of the Gas-Lubricated Bearing in Optical Lithography,” Tribol. Int., 39(11), pp. 1336–1341. [CrossRef]
Li, Y., and Ding, H., 2007, “Influences of the Geometrical Parameters of Aerostatic Thrust Bearing With Pocketed Orifice-Type Restrictor on Its Performance,” Tribol. Int., 40(7), pp. 1120–1126. [CrossRef]
Jeng, Y. R., and Chang, S. H., 2013, “Comparison Between the Effects of Single-Pad and Double-Pad Aerostatic Bearings With Pocketed Orifices on Bearing Stiffness,” Tribol. Int., 66, pp. 12–18. [CrossRef]
Wang, N., and Cha, K. C., 2010, “Multi-Objective Optimization of Air Bearings Using Hypercube-Dividing Method,” Tribol. Int., 43(9), pp. 1631–1638. [CrossRef]
Chang, S. H., and Jeng, Y. R., 2014, “A Modified Particle Swarm Optimization Algorithm for the Design of a Double-Pad Aerostatic Bearing With a Pocketed Orifice-Type Restrictor,” ASME J. Tribol., 136(2), p. 021701. [CrossRef]
Belforte, G., Raparelli, T., Trivella, A., Viktorov, V., and Visconte, C., 2006, “Numerical Analysis on the Supply Hole Discharge Coefficient in Aerostatic Bearings,” International Conference on Tribology, Parma, Italy, Sept. 20–22, Paper No. AITC-AIT 2006.
Eleshaky, M. E., 2009, “CFD Investigation of Pressure Depressions in Aerostatic Circular Thrust Bearings,” Tribol. Int., 42(7), pp. 1108–1117. [CrossRef]
Nishio, U., Somaya, K., and Yoshimoto, S., 2011, “Numerical Calculation and Experimental Verification of Static and Dynamic Characteristics of Aerostatic Thrust Bearings With Small Feedholes,” Tribol. Int., 44(12), pp. 1790–1795. [CrossRef]
Belforte, G., Raparelli, T., Viktorov, V., and Trivella, A., 2007, “Discharge Coefficients of Orifice-Type Restrictor for Aerostatic Bearings,” Tribol. Int., 40(3), pp. 512–521. [CrossRef]
Miyatake, M., and Yoshimoto, S., 2010, “Numerical Investigation of Static and Dynamic Characteristics of Aerostatic Thrust Bearings With Small Feed Holes,” Tribol. Int., 43(8), pp. 1353–1359. [CrossRef]
Neves, M. T., Schwarz, V. A., and Menon, G. J., 2010, “Discharge Coefficient Influence on the Performance of Aerostatic Journal Bearings,” Tribol. Int., 43(4), pp. 746–751. [CrossRef]
Senatore, A., D'Agostino, V., Di Giuda, R., and Petrone, V., 2011, “Experimental Investigation and Neural Network Prediction of Brakes and Clutch Material Frictional Behaviour Considering the Sliding Acceleration Influence,” Tribol. Int., 44(10), pp. 1199–1207. [CrossRef]
Gyurova, L. A., and Friedrich, K., 2011, “Artificial Neural Networks for Predicting Sliding Friction and Wear Properties of Polyphenylene Sulfide Composites,” Tribol. Int., 44(5), pp. 603–609. [CrossRef]
Kurban, A. O., and Yildirim, S., 2003, “Analysis of a Hydrodynamic Thrust Bearing With Elastic Deformation Using a Recurrent Neural Network,” Tribol. Int., 36(12), pp. 943–948. [CrossRef]
Chang, Y. Z., and Wang, N., 2005, “Tribological Performance Prediction Using an Artificial Neural Network Optimized by the DIRECT Algorithm,” ASME Paper No. WTC2005-63413. [CrossRef]
Tsai, C. M., and Wang, N., 2007, “An Assessment of Neural Network Metamodels for Thermohydrodynamic Lubrication Analysis,” Society of Tribologists and Lubrication Engineers (STLE) 62nd Annual Meeting, Philadelphia, PA, May 6–10.

Figures

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Fig. 1

Aerostatic bearing with inherent orifice-type restrictor

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Fig. 2

Mesh for an aerostatic bearing (h = 9 μm, Rb = 20 mm, D = 3 mm, d = 0.2 mm, α = 118 deg, and l = 0.3 mm)

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Fig. 3

Convergence test of CFD simulation (h = 9 μm, Rb = 20 mm, D = 3 mm, d = 0.2 mm, α = 118 deg, l = 0.3 mm, and Ps = 0.5 MPa)

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Fig. 4

The comparison of CFD simulations and experimental results (Rb = 20 mm, D = 3 mm, d = 0.23 mm, α = 118 deg, l = 0.3 mm, and Ps = 0.5 MPa)

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Fig. 5

Comparison of FDM calculations and CFD simulations (Rb = 20 mm, D = 3 mm, d = 0.2 mm, α = 118 deg, l = 0.3 mm, and Ps = 0.5 MPa)

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Fig. 6

Schematic of a three-layer feed-forward neural network (2-6-4-1 network)

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Fig. 7

Influence of orifice diameter on the discharge coefficient (Rb = 20 mm, D = 3 mm, α = 118 deg, l = 0.3 mm, and Ps = 0.5 MPa)

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Fig. 8

Influence of supply pressure on the discharge coefficient (d = 0.1 mm, Rb = 20 mm, D = 3 mm, α = 118 deg, and l = 0.3 mm)

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Fig. 9

Influence of bearing radius on the discharge coefficient (d = 0.1 mm, D = 3 mm, α = 118 deg, Ps = 0.5 MPa, and l = 0.3 mm)

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Fig. 10

Influence of supply orifice length on the discharge coefficient (d = 0.1 mm, Rb = 20 mm, D = 3 mm, α = 118 deg, Ps = 0.5 MPa, and h = 10 μm)

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Fig. 11

Influence of supply passage diameter on the discharge coefficient (d = 0.1 mm, Rb = 20 mm, l = 0.3 mm, Ps = 0.5 MPa, and h = 10 μm)

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Fig. 12

Predictions of discharge coefficients from the 2-6-4-1 network

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Fig. 13

Comparison of FDM calculations and CFD simulation (Rb = 20 mm, d = 0.1 mm, D = 3 mm, α = 118 deg, Ps = 0.5 MPa, l = 0.3 mm, and h = 8 μm)

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