Dependent failure

So far it has been assumed that the primary events of a fault tree are independent of one another. However, this is not always true. Failures of components from the same production may occur due to a manufacturing flaw which affects all of them. A corrosive atmosphere may shorten the lifetimes of all components exposed to it. Errors in testing and maintenance may occur, for example an erroneous calibration of several redundant measuring devices. These examples belong to a class of failures called dependent failures . They are discussed in detail in [48]. Dependent failures are failures which occur simultaneously or within a short interval of time so that several components are not available simultaneously. This type of failures is especially grave if it affects redundant sub-systems or systems. An overview of the different types of failures is provided by Fig. 9.33. 

In general three types of dependent failures are distinguished  

In order to adequately treat dependent failures in a reliability analysis, secondary failures (1) and failures of components due to functional dependencies (2) are accounted for as far as possible by a detailed fault tree model. Common cause failures (3) require a separate treatment. The procedure for aU three failure types is explained below. Yet, before that possible causes of dependent failures are classified. 

A classification of dependent failures is helpful for their analysis. According to [49] we distinguish the following causes  

Planning errors cause wrong designs and construction flaws and lead to wrong or insufficient instructions in the operating manual. Planning errors stem, for example, from mutual dependencies which have not been identified or sufficiently accounted for as the dependence of human error probabilities on environmental influences or impairment of components due to changes in environmental conditions caused by an accident. 

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Flexural stress SiC mpture curves are shown in Figure 3 (27). AU. the forms tend to be fairly resistant to time-dependent failure by elevated temperature creep. In addition, SiC shows outstanding resistance to oxidation even at 1200°C as a result of formation of a protective high purity siUca surface layer (28). 

This FMEA/FMECA shows failure rates that are both demand and time dependent. Adding the demand failure rates gives a train failure rate of 5. 1 E-3/demand. The sum of the time dependent failure rates is 3Ei-10/hr. A standby system such as this, does not exhibit its operability until it is actuated for which the probability is needed that the train has failed since the last use Val " are considered to be part o ng envelope and... 

Thi.s method assumes that X, the total constant failure rate for each unit, can be expanded into independent and dependent failure contributions (equation... 

Fleming et al. (1985) define this as similar to the model of Marshall and Olkin (1967) except that BPM is only for time-dependent failure rates. Equations 3.5.8-la-d are for four parameters, but the method may be generalized to n components. These parameters may be related to the MGL parameters as shown in equations 3.5.8-2a-d. 

Table 3.6-4 Computer Codes for Dependent-Failure A nalysis...

SETS FtUi J f. . rid). [. G 8). Adds generic causes and links to fault tree cutsets that include one or more generic causes are obtained and identified as common-cause candidates Can handle large fault trees and can identify partial dependency in cutsets attractive features of SETS as cut-set generator justify use for dependent failure analysis CDC 7600. AvaiJjhle Ifofn Argonne Softw-ie I en-i- r... 

There are two reliability modeling codes used for Tech. Spec, modification to address time-dependent failure rate and repair FRANTIC developed by BNL/NRC and SOCRATES developed by BCl,/EPRI. 

Soufc. No. of failures No. of demands or service time Test interval No. of maintenances No. of dependent failures Failure rate Failures/ demand Repair lime... 

It is unclear whether previously published fire risk analyses have adequately ircaicd dependent failures and systems interaetions. Examples of either experienced or postulated system interactions that have been missed include unrelated systems that share common locations and the attendant spatially related physical interactions arising from fire. Incomplete enumeration of causes of failure and cavalier assumptions of independence can lead to underestimation of accident l rci uencies by many orders of magnitude,... 

Loc.ttion and the elevation are important in flooding analysis. Codes such as COMCAN HI or SETS for dependent failure analysis listed in Table 3.6-4 may be used for locating components that would be affected by flooding. These codes. serve this purpose with a complex component identifier for location and elevation. 

Analysis of Dependent Failure Events and Failure Events Caused by Harsh Environment Conditions Nuclear 700 events representing common cause failures and failures caused by harsh environments Licensee Event Reports on failures of 26 component and subcomponent types listed below 94. 

TITLE Analysis of Dependent Failure Events and Failure Events Caused by... 

In the analysis of pumps, IPRDS failure data for 60 selected pumps at four nuclear power plants were statistically analyzed using FRAC. The data cover 23 functionally different pumps, respectively, for two BWRs. Catastrophic, degraded, and incipient failure severity categories were considered for both demand-related and time-dependent failures. 

The second limitation is the life dispersion of machinery components. It is difficult to predict time-dependent failure modes because even they do not occur at the exact same operating intervals. Consider the life dispersion of mechanical gear couplings on process compressors. Both components are clearly subject to wear. If we conclude that their MTBF (mean-time between failure), or mean-time-between-reaching-of-detect-limit is 7.5 years, it is possible to have an early failure after 3 years and another... 

Since most time-dependent failures have larger life dispersions, we must consider the maximum and minimum ratios of 4 1 and 40 1. Generally, relative life dispersion increases with the absolute value of MTBF. That is, wear items with a relatively short life expectancy such as rider rings on reciprocating compressors will have a comparatively smaller dispersion than components such as gear tooth flanks, which can be expected to remain serviceable for long periods of time. 

The existence of a wedge-shaped cavitated or fibrillar deformation zone or craze, ahead of the crack-tip in mode I crack opening, has led to widespread use of models based on a planar cohesive zone in the crack plane [39, 40, 41, 42]. The applicability of such models to time-dependent failure in PE is the focus of considerable attention at present [43, 44, 45, 46, 47]. However, given the parallels with glassy polymers, a recent static model for craze breakdown developed for these latter, but which may to some extent be generalised to polyolefins [19, 48, 49], will first be introduced. This helps establish important links between microscopic quantities and macroscopic fracture, to be referred to later. 

The purpose of the research introduced here is to approach closely to the failure mechanism of rubbery polymers from a phenomenological view. Many of excellent observations on the time dependent failure behavior of rubbery polymers have been done by those scientists, T. L. Smith (5> 6, 7) F- Bueche (8),... 

Evans, A. G. 1972. A method for evaluating the time-dependent failure characteristics of brittle materials - and its application to polycrystalline alumina, J. Mater. Sci., 7, pp. 1137-1146. 

In view of fact that most time-dependent failures, such as the fatigue of polymers, initiate at the surface, more precisely at the interface of the polymer and the surrounding medium, it is to be expected that the application of plasma polymers will contribute to the improvement of the wear characteristics of polymers at least in certain cases. 

Transfer Lines with No Inventory Banks Time-Dependent Failures... 

Consider a transfer line with m stages or stations. The station failures can be either time dependent (failure is possible when the station is idling) or operation dependent (failure only occurs when the station is working on a part). 

Two limiting cases are of interest (1) operation-dependent failures dj = ft = 0, and (2) time-dependent failures dj = Oj, dj = fl2- For operation-dependent failures and identical stations. 

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