Test verification and leakage rate prediction method

Tests were performed on a fully automatic testing machine for gasket performances, and the specific details on the test machine and test procedure can be found in the reference (Gu et al., 2007b). The test conditions are listed in Table 12.

Sample Quantity

Sample

Dimension

(mm)

Test Medium

Gasket Seating Stress (MPa)

Gas Pressure Difference (106 Pa)

Test

Temperature

(K)

3

ф109хф61х2

99.9% nitrogen

20, 30, 40, 50, 60

1, 2, 3, 4.5, 6

293

Table 12. Conditions for the leakage test

The relationship between medium pressure difference p1-p2 and leakage rate L under different gasket seating stresses as is shown in Fig. 26, in which symbols represent experimental data, and curves are plotted according to the leakage model. The experimental results show that the leakage rate increases obviously with the increase of the test medium pressure when the gasket seating stresses are smaller. On the contrary, when the gasket seating stresses are larger, this tendency is not obvious. The variation of leakage rates with pressure difference across gasket width follows precisely the curves represented by the leakage model, as indicated by the high value of the correlation coefficient R which is nearly equal to unity.

Test verification and leakage rate prediction method

Test pressure difference (pi-p2) (MPa)

Fig. 26. Relationship between leakage rate and test pressure difference under different seating stresses

The coefficients Al, Am, nL and nM in Eq. (55) can be obtained by regression analysis of the experimental data, and they are listed in Table 13. According to Eq. (55) and the regression coefficients, the relationships between the pressure difference and the leakage rate under different gasket compressive stresses are obtained, and they are also illustrated in Fig. 26.

Al

Am

nL

Пм

R

8.52х10-23

2.79х10-12

4.08

3.06

0.984

Table 13. Regression coefficients in Eq. (55)

Подпись: L = Подпись: Г Pm + AM Подпись: O'"" (P1 -P2 ) P2 a0 ) l D1 Подпись: (56)
Test verification and leakage rate prediction method

According to Eq. (55) and the regression coefficients in Table 13, the leakage rates of other gases leaking through non-asbestos gaskets with different sizes and used under various working conditions can also be predicted. It can be assumed that the leakage paths in gaskets are distributed uniformly in the circumferential direction. The larger the gasket perimeter, the more the leakage paths are. Therefore, when the leakage rate prediction is performed for the gaskets with different sizes, the correction of Eq. (56) is necessary, and hence, the leakage prediction formula holds:

where Dl and D2 are diameters of the tested gasket and the gasket on which the leakage rate will be predicted, respectively.

It can be seen from Eq. (55) and Eq. (56) as well that the total leakage rate of gases through non-asbestos gaskets is the sum of the laminar flow rate and the molecular flow rate. The leakage is mainly the molecular flow when the gasket seating stress is large and the gas pressure is low, and the leakage rate is directly proportional to the pressure difference (P1- p2). On the contrary, when the gasket seating stress is small and the gas pressure high, the leakage is predominantly the laminar flow. In this case, the leakage rate is in direct proportion to the square difference of pressures (P12-P22), and the influence of the molecular flow can be ignored. The latter situation represents the leakage state of gasket sealing joints in most pressure vessels and piping.

2. Conclusions

Two kinds of non-asbestos sealing composites were developed by using aramid, glass, and pre-oxidized carbon fibers as reinforcing fibers, and nitrile rubber and natural rubber as binders. Design of these composites as well as preparation techniques were discussed. The surface treatment effects of fibers by using such methods as immersion coating, surface oxidation and plasma treatments were investigated. The results of the transverse tensile test and the SEM analysis reveal that the surface pretreatment can largely enhance the associative strength of the interface between fiber and matrix.

Both the molding and the calendaring preparation processes of NASC were presented. Contents of main compositions of two kinds of NASC were determined by uniform design and regression design methods in which the transverse tensile strength, compressibility, resilient rate and stress relaxation rate of the composites were used as evaluation indexes. According to the data resulted from mixing regression design experiments, the regression equation was obtained.

Methods for measuring and characterizing the micro structural parameters including the aspect ratio, orientation, distribution of short fibers, interphase thickness, and porosity of NASC were discussed. The short fiber aspect ratio can be obtained by measuring the dimensions of the fibers that were separated from the composite, and results can be evaluated by the mean aspect ratio method, the histogram method and the distribution function method. The short fiber orientation can be tested by the section-analysis method and the plane-observation method, and results can be evaluated by the distribution function method, the histogram method and the modified coefficient method.

The micromechanical model of a single fiber cylindrical cell, which includes fiber, matrix and their interphase, was established. The stress transfer mode among the fiber, the matrix and the interphase was investigated, and the stress distributions in them were obtained. A model of a compressive type single-fiber cell was established, and the prediction methods for the stress-strain relationship, the tensile module, the longitudinal tensile strength, the transverse tensile strength, the compression-resilience performance and the creep behavior were proposed.

A series of tests for tensile property, compressibility, resilient rate, and stress relaxation property of NASC were conducted. The experimental results were compared with the predicted values. The predicted stress-strain relationship of NASC is in good agreement with the experimental result when the strain of the composite is relatively small, while the error is obvious when the strain is relatively large. The transverse tensile strength increases with the increase of the fiber volume content and the mean aspect ratio and decreases with the increase in the test temperature. All the experimental results are smaller than those predicted, and the maximum error between them is about 13%. The compressibility increases with increasing the maximum compressive stress and decreasing the fiber volume content, while the resilient rate decreases with the increase in the maximum compressive stress and the fiber volume content. They are nearly irrelevant to the fiber mean aspect ratio and orientation. The errors both between the predicted compressive rates and experimental data and between the predicted resilient rates and the experimental results are less than 15%. At the beginning of the stress relaxation, the stress in the composite decreases quickly, the stress relaxation speed decreases essentially after 80 to 100 minutes, and the stress relaxation curve trends to be a straight line. The stress relaxation rate increases with increasing initial stress and temperature and decreasing fiber volume content. Such microstructure parameters as fiber mean aspect ratio and orientation have less evident influence on the stress relaxation property of NASC. The experimental and predicted results are basically identical, and the maximum error is about 8.5%, which indicates that the stress relaxation property of NASC can be well evaluated by the stress relaxation equation presented in this chapter.

A leakage model was developed to predict non-asbestos gasket leakage rates with different gasket sizes and various gases under different working conditions. The model is constructed on the base of the gasket leakage tests conducted over a nitrogen pressure range of 1 to 6 MPa and a gasket seating stress range of 20 to 60 MPa. The established model gives relatively accurate predictions, but it is necessary to conduct additional tests before predicting leakage rate of other types of gaskets. High temperature will cause the deterioration of sealing materials and result in the increase of leakage rates, which has not been taken into consideration in the present model, and this subject should be studied.

3. Acknowledgement

This work was supported by the National Natural Science Foundation of China (Grant No. 10872088) and the Doctoral Foundation of the Ministry of Education of China (Grant No. 20070291004 and No. 20093221120009). The authors of this chapter gratefully acknowledge the corresponding government organizations for the funds that made this project possible. We would also like to thank those postgraduate students who participated in our previous work throughout these years and made the contribution in the aspect of material preparation, performance test, data processing, and so on.

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