Environmental Engineering Reference
In-Depth Information
Table 2.2 Results of comparison 
Data on
failures (age,
criticality)
Data on the
nature of
failure
Data on
repairs and
TM
Data on
loading
Model
Parameters
Linear
τ, β
+
-
-
+
Linear for com-
peting failures
τ, β, Τ 0
+
+
-
+
Weibull
β, η
+
-
-
+
Weibull for
competing
failures
β, η, η 0 , Τ 0
+
+
-
+
Uniform wear
λ 0 , ω, Ν
+
+
+
+
tests must be appropriately adapted together with appropriate preparation
of the input data.
Given the above difficulties, Atwood et al. 34 recommend to choose
the simplest two-parameter model of reliability and accurate approach to
calculation of parameters, uncertainty analysis and extrapolation of the
results.
Depending on the application of the PSA results, the initial data on the
values of unavailability of elements can be represented as point or averaged
over a certain range of time estimates. Average values of unavailability for
a period of one year are used in most cases. It should be noted that for
the elements in operating or standby mode unavailability is a function of
time, even at a constant failure rate. For example, in RiskSpectrum 47 the
unavailability for the elements in the standby mode is calculated as:
q ( t ) = 1-exp (-λ Τ ) ≈ λ Τ /2,
[2.25]
where λ is the failure rate in the standby mode, Τ is the interval of periodic
testing.
The unavailability function of an element failure rate governed by
Weibull law [2.23] with different assessments is analysed in Ref. 42:
• the point estimate of the before test unavailability (BTU)) - the
maximum value of unavailability in the interval ( n - 1) T < t < nT ;
• maximum before test unavailability (MBTU) - the maximum BTU
per lifetime;
• point estimate of the forty-year value (FYV)) - BTU value in 40 years;
• average interval unavailability (AIU)) - the average estimate in the
range;
• maximum average interval unavailability (MAIU)) - the maximum
value of AIU for the entire term of service;
• year average unavailability (YAU)) - average estimate over a period
of one year;
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