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Research Papers: Design and Analysis

On the Use of Gas Flow Models to Predict Leak Rates Through Sheet Gasket Materials

[+] Author and Article Information
Abdel-Hakim Bouzid

Professor
Fellow ASME
Department of Mechanical Engineering,
Ecole de Technologie Superieure,
1100 Notre-Dame Ouest,
Montreal, QC H3C 1K3, Canada
e-mail: hakim.bouzid@etsmtl.ca

Ali Salah Omar Aweimer

Department of Mechanical Engineering,
Ecole de Technologie Superieure,
1100 Notre-Dame Ouest,
Montreal, QC H3C 1K3, Canada
e-mail: Ali-salah-omar.aweimer.1@etsmtl.ca

1Corresponding author.

Contributed by the Pressure Vessel and Piping Division of ASME for publication in the JOURNAL OF PRESSURE VESSEL TECHNOLOGY. Manuscript received September 22, 2017; final manuscript received June 14, 2019; published online July 17, 2019. Editor: Young W. Kwon.

J. Pressure Vessel Technol 141(5), 051204 (Jul 17, 2019) (9 pages) Paper No: PVT-17-1189; doi: 10.1115/1.4044115 History: Received September 22, 2017; Revised June 14, 2019

The prediction of leak rate through porous gaskets for different gases based on test conducted on a reference gas can prevent bolted joint leakage failure and save the industry lots of money. This work gives a basic comparison between different gas flow models that can be used to predict leak rates through porous gasket materials. The ability of a model to predict the leak rate at the micro- and nanolevels in tight gaskets relies on its capacity to incorporate different flow regimes that can be present under different working conditions. Four models based on Navier–Stokes equations that incorporate different boundary conditions and characterize specific flow regime are considered. The first- and second-order slip, diffusivity, and molecular flow models are used to predict and correlate leak rates of gases namely helium, nitrogen, SF6, methane, argon, and air passing through three frequently used porous gasket materials which are flexible graphite, polytetrafluoroethylene (PTFE), and compressed fiber. The methodology is based on the determination experimentally of the porosity parameter (N and R) of the microchannels assumed to simulate the leak paths present in the gasket using helium as the reference gas. The predicted leak rates of different gases at different stresses and pressure levels are confronted to the results obtained experimentally by measurements of leak rates using pressure rise and mass spectrometry techniques. The results show that the predictions depend on the type of flow regime that predominates. Nevertheless, the second-order slip model is the one that gives better agreements with the measured leaks in all cases.

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References

Gu, B. Q. , 1999, “ Application of Model of Gases Flowing Through Porous Media to Gasket Sealing,” J. Nunjing Univ. Chem. Technol., 21(1), pp. 19–22 (in Chinese).
Wang, S. , 2000, “ Sealing Model of Nonmetallic Gaskets and Calculation of Leakage Rate of Bolted Flanged Connections,” Master thesis, Nanjing University of Technology, Xuanwu District, China.
Payne, J. R. , 1985, “PVRC Flanged Joint User Survey,” Welding Research Council, New York, WRC Bulletin 309.
Shabtai, A. , Elovici, Y. , and Rokach, L. , 2012, A Survey of Data Leakage Detection and Prevention Solutions, Springer Science & Business Media, New York.
Masi, V. , Bouzid, A. , and Derenne, M. , 1998, “ Correlation Between Gases and Mass Leak Rate of Gasketing Materials,” 1998 ASME/JSME PVP Conference, San Diego, CA, PVP Vol. 367, Analysis of Bolted Joints, pp. 17–24.
Jolly, P. , and Marchand, L. , 2009, “ Leakage Predictions for Static Gasket Based on the Porous Media Theory,” ASME J. Pressure Vessel Technol., 131(2), p. 021203. [CrossRef]
Grine, L. , and Bouzid, A. , 2011, “ Correlation of Gaseous Mass Leak Rates Through Micro and Nanoporous Gasket,” ASME J. Pressure Vessel Technol., 133(2), p. 021402. [CrossRef]
Grine, L. , and Bouzid, A. , 2011, “ Liquid Leak Predictions in Micro and Nano Porous Gaskets,” ASME J. Pressure Vessel Technol., 133(5), p. 051402. [CrossRef]
Kazeminia, M. , and Bouzid, A. , 2016, “ Predicting Leakage in Packed Stuffing Boxes,” 23rd International Conference on Fluid Sealing, BHR Group, Manchester, UK, Mar. 2–3, pp. 45–59.
Dongari, N. , and Agrawal, A. , 2012, “ Modeling of Navier–Stokes Equations for High Knudsen Number Gas Flows,” Int. J. Heat Mass Transfer, 55(15–16), pp. 4352–4358. [CrossRef]
Beskok, A. , and Karniadakis, G. , 1999, “ A Model for Flows in Channels, Pipes, and Ducts at Micro and Nano Scales,” J. Microscale Thermophys. Eng., 3(1), pp. 43–77. [CrossRef]
Xue, H. , Fan, Q. , and Shu, C. , 2000, “ Prediction of Micro-Channel Flows Using Direct Simulation Monte Carlo,” J. Probab. Eng. Mech., 15(2), pp. 213–219. [CrossRef]
Sbragaglia, M. , and Succi, S. , 2005, “ Analytical Calculation of Slip Flow in Lattice Boltzmann Models With Kinetic Boundary Conditions,” J. Phys. Fluids, 17(9), p. 093602. [CrossRef]
Aweimer, A. S. O. , and Bouzid, A.-H. , 2019, “ Evaluation of Interfacial and Permeation Leaks in Gaskets and Compression Packing,” ASME J. Nucl. Eng. Radiat. Sci., 5(1), p. 011013. [CrossRef]
Haruyama, S. , Nurhadiyanto, D. , Choiron, M. A. , and Kaminishi, K. , 2013, “ Influence of Surface Roughness on Leakage of New Metal Gasket,” Int. J. Pressure Vessels Piping, 111–112, pp. 146–154. [CrossRef]
Boqin, G. , Ye, C. , and Dasheng, Z. , 2007, “ Prediction of Leakage Rates Through Sealing Connections With Nonmetallic Gaskets,” Chin. J. Chem. Eng., 15(6), pp. 837–841. [CrossRef]
Djordjevic, V. , 2008, “ Modeling of the Slip Boundary Condition in Micro-Channel/Pipe Flow Via Fractional Derivative,” Monogr. Acad. Nonlinear Sci., 2, pp. 136–158. http://www2.masfak.ni.ac.rs/uploads/articles/www2_004kor_vladan_djordjevic_engleski.pdf
Abid, M. , Chattha, J. A. , Khan, K. A. , and Wajid, H. A. , 2014, “ Sealing Performance of Gasketed Flange Joints–a Parametric Study,” IIUM Eng. J., 15(2), pp. 59–67. [CrossRef]
Kobayashi, T. , Nishida, T. , and Yamanaka, Y. , 2002, “ Simplified Sealing Test Procedure of Gaskets Based on Compressive Strain,” ASME Paper No. PVP2002-1079.
Marchand, L. , Derenne, M. , and Masi, V. , 2005, “ Predicting Gasket Leak Rates Using a Laminar-Molecular Flow Model,” ASME Paper No. PVP2005-71389.
Tison, S. A. , 1993, “ Experimental Data and Theoretical Modeling of Gas Flows Through Metal Capillary Leaks,” Vacuum, 44(11–12), pp. 1171–1175. [CrossRef]
Maurer, J. , Tabeling, P. , Joseph, P. , and Willaime, H. , 2003, “ Second-Order Slip Laws in Microchannels for Helium and Nitrogen,” Phys. Fluids, 15(9), pp. 2613–2621. [CrossRef]
Araki, T. , Kim, M. S. , Iwai, H. , and Suzuki, K. , 2002, “ An Experimental Investigation of Gaseous Flow Characteristics in Microchannels,” Nanoscale Microscale Thermophys. Eng., 6 (2), pp. 117–130. [CrossRef]
Dongari, N. , Sharma, A. , and Durst, F. , 2009, “ Pressure-Driven Diffusive Gas Flows in Micro-Channels: From the Knudsen to the Continuum Regimes,” Microfluid. Nanofluid., 6(5), pp. 679–692. [CrossRef]

Figures

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Fig. 1

Capillary model with the second-order slip flow

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Fig. 2

Universal ROTT test rig

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Fig. 3

Prediction of argon leak rates with different models for compressed fiber at (a) 7 and 28 MPa and (b) 42, 55, and 69 MPa

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Fig. 4

Prediction of methane leak rates with different models for compressed fiber at (a) 7 and 28 MPa and (b) 42, 55, and 69 MPa

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Fig. 5

Prediction of SF6 leak rates with different models for compressed fiber at (a) 7 and 28 MPa and (b) 42, 62, and 83 MPa

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Fig. 6

NR4 parameter for compressed fiber

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Fig. 7

Percentage void surface for compressed fiber

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Fig. 8

Prediction of argon leak rates with different models for flexible graphite at (a) 7 and 28 MPa and (b) 42, 62, and 83 MPa

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Fig. 9

Prediction of methane leak rates with different models for flexible graphite at (a) 7 and 28 MPa and (b) 42, 62, and 83 MPa

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Fig. 10

Prediction of SF6 leak rates with different models for flexible graphite at (a) 7 and 28 MPa and (b) 42, 62, and 83 MPa

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Fig. 11

NR4 parameter for flexible graphite

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Fig. 12

Percentage of void surface percentage for flexible graphite

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Fig. 13

Prediction of (a) air, (b) nitrogen, and (c) argon leak rates with different models for PTFE at 27.6 and 55.2 MPa

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Fig. 14

NR4 parameter for PTFE gasket

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Fig. 15

Percentage of void surface for PTFE for different stresses

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