Analysis of sodium valve reliability data at CREDO. [LMFBR] Page: 5 of 13
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Table 2 (columns 2 and 3) lists the calculated values of the MLE and
interval estimates of A for valves of different types and for different
failure modes. Because of the rather wide site-to-site variations in
maintenance and operating procedures and conditions, there is no attempt
to combine data from different sites. The numerical estimates are comparable
to those reported in the literature for water and steam valves. (Typical
values reported for water and steam valves, which were summarized in Ref. 2,
_ r c
ranged from about 1 x 10 to 30 x 10 per hr.) A more detailed categori-
zation by failure mode and design characteristics was presented for LMEC,
THORS, MSAR and EBR-II in Ref. 2. More recently collected data are being
examined for significant trends, but in most cases, the valves at any given
site are of the same basic design and experienced one predominant failure mode.
Although the assumption of exponential failure behavior is commonly
made for mechanical components, and may be adequate for many applications,
there is a great deal of interest in identifying the variation of failure
rate with time. Careful consideration of time-dependent failure behavior
along with maintenance practices can help to optimize preventive maintenance
and lead to increased system availability. The hazard plotting technique
of Nelson9 was used to identify potential time-dependent variation in failure
rates. In this technique, the data, are displayed on graphs of time-to-failure
vs. cumulative hazard H(x). Basically, if the data fall more or less along
a straight line on linear paper, the failure distribution is well modeled as
exponential and the failure rate A is estimated by the slope of the line.
If the data are approximately linear on log-log (Weibull) paper, the failure
distribution can be represented by a Weibull model, i.e.,
fix) - vv(x/“)6-
The shape parameter e and scale parameter A can then be estimated from the
The data sets in Table 2 were plotted on both linear and Weibull paper.
Column 4 of Table 2 lists the value of A estimated (by least-squares fit)
from the linear plots. Most of the plots for data sets with more than a few
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Bott, T F & Haas, P M. Analysis of sodium valve reliability data at CREDO. [LMFBR], article, January 1, 1979; Tennessee. (https://digital.library.unt.edu/ark:/67531/metadc1100705/m1/5/: accessed March 18, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.