Generic data base

Generic Data Base lor Data and Models Chapter of the National Reliability Evaluation Program Guide... 

Oswald, A. J. Generic Data Base and Models Chapter of the National Reliability Evaluation Program (NREP) Guide. EG G Idaho, Inc., EGG-EA-5887, June 1982. 

The CCPS Taxonomy developed for this book is one step toward accumulating and collating equipment reliability data for the CPI. Ideally, it will be expanded and modified as more companies make chemical process equipment failure rates and reliability data available. We expect that CCPS will update this book and the CCPS generic data base as new information becomes available. The taxonomy may also require modification where experience shows it is needed. We would appreciate any contribution from readers to these ends. 

In fact. In order for the generic data base to be a viable approach, the following assumptions must be accepted. 

Although such predictive techniques would be generally welcomed by regulators, industrial scientists, and academicians, the contradictory nature of some of the material in these three chapters reflects the current status of such research, i.e., the final answer on predictive techniques and a generic data base is not in yet. Much discusrion is needed before moving from these first generation data bases to a common, functional, well-received second generation data base. 

The data is used in accordance with the guidance in NUREG/CR-2815 (Reference 5), and basic failure rate data is obtained from the EPRI ALWR Requirements Document (Reference 6) supplemented with data from the NREP Generic Data Base (Reference 7) and other nuclear sources. Maintenance and repair times are calculated as outlined in NUREG/CR-2815. The inspection and test times and frequencies are as specified in the System 80+ LCDs (See CESSAR-DC Chapter 16). 

The type and degree of detail of the database is determined by the intended use of detail of the evaluation. For a general evaluation, a generic data base might be sufficient. But, for a systematic evaluation of the level of plant safety and for an optimal maintenance programme, a plant specific data base is generally required. 

In Table 1, the value of the linear ageing factor (a) has been obtained from a generic data base, which is known as TIRGALEX (Levi et al., 1998). TIRGALEX considers that the value of a in the case of motor-operated valves is equal to 4.11 10 " hr. Furthermore, the value of Test interval (T) is taken from current Surveillance Requirements in Technical Specifications, which impose an operational test of this MOV at least... 

The MITI-sponsored used the standard PSA approach (small event trees/large fault trees), THERP for human reliability calculation and the US generic data base except for Japanese-specific data for DCs. The final results were not available. The interim results for PWR and BWR plants are as follows ... 

Table 2.6-6. Statistical Analyses and Generic Data Bases...

Where field data were imavailable, a program of experimental work (for example, based on the use of simulators for control room operations) could be implemented to generate appropriate generic data. 

Chapter 4—Data Bases, Sources, and Studies Summarizes and characterizes several generic data resources available to risk analysts and process engineers in the CPI. It includes a discussion of the resource search and selection process and the presentation format for the information on resources. 

Chapter 5—CCPS Generic Failure Rate Data Base Contains tables of generic process equipment reliability data that are structured by the CCPS Taxonomy. The data are extracted from data resources in Chapter 4. The chapter includes a discussion of the selection, treatment, and presentation of the data in the Tables. 

Chapter 7—Failure Rate Data Transfer Provides a form to facilitate the transfer of plant-specific data to the CCPS Data Base or to combine it with other generic data. 

When plant-specific data are required. Chapter 6 discusses how to collect and treat the data so that the resulting failure rates can be used in a CPQRA or be combined with the data in the CCPS Generic Failure Rate Data Base. Chapter 7 provides a form that can be used to transfer these data to CCPS s Generic Failure Rate Data Base. 

However, the data that are contributed to a generic failure rate data base are rarely for identical equipment and may represent many different circumstances. Generic data must be chosen carefully because aggregating generic and plant-specific data may not improve the statistical uncertainty associated with the final data point, owing to change in tolerance. 

Many data cells in the CCPS Taxonomy use equipment boundaries found in available generic data sets in which equipment and service is similar to that in the CPI. The boundaries established for other data cells were generally combinations of normal equipment modules—such as pump, seals, coupling, motor and base plate, or refrigeration units—and functionally interdependent basic and auxiliary components, such as motor controllers. Boundaries may change as greater amounts of equipment reliability data become available. 

Real-time access to the data base is possible through a data base management system. In addition to safety-related system data, data for interfacing (auxiliary) system components are also available. The data base management system provides in-depth flexibility for generation of specific output reports. Although access has been limited to members of the Swedish Utility Consortium and the Swedish Power Board Directorate, a Reliability Data Book is available with generic failure rates based primarily on this data base. 

Three reports have been issued containing IPRDS failure data. Information on pumps, valves, and major components in NPP electrical distribution systems has been encoded and analyzed. All three reports provide introductions to the IPRDS, explain failure data collections, discuss the type of failure data in the data base, and summarize the findings. They all contain comprehensive breakdowns of failure rates by failure modes with the results compared with WASH-1400 and the corresponding LER summaries. Statistical tables and plant-specific data are found in the appendixes. Because the data base was developed from only four nuclear power stations, caution should be used for other than generic application. 

The LER data base served as the primary source of DG failure data, while a data base for DG successes was formed from nuclear plant licensees responses to a USNRC questionnaire (Generic Letter 84-15). Estimates of DG failure on demand were calculated from the LER data, DG test data, and response data from the questionnaire. The questionnaire also provided data on DG performance during complete and partial LOSP and in response to safety injection actuation signals. Trends in DG performance are profiled. The effects of testing schedules on diesel reliability are assessed. Individual failures are identified in an appendix. 

Generic data set based on plant and industry failure reports over a ten-year span... 

The generic data sources used in the BRP data base originate from the nuclear industry. 

The review of the data portion of the Indian Point 2 (IP2) and 3 (IPS) PRA (a 1982 internal document prepared by Consolidated Edison and the New York Power Authority) is confined to the plant-specific and generic component failure and service hour data sections because these were the only segments available to the reviewers. The LERs produced during a ten-year span of IP2 s operation were evaluated to determine their applicability to the PRA data needs. It was eventually decided to use only the LERs generated after IP2 became critical (from May 23, 1973 to December 31, 1979) for the component data base development, based on the availability of failure event information and more uniform operability, testing, and reporting criteria. 

Opening segments of the IP2 PRA data analysis section describe the definitions of terms and concepts employed, the assumptions made, and limitations recognized during the data base construction. A set of 39 plant-specific component failure mode summaries established the basis for component service hour determinations, the number of failures, and the test data source for each failure mode given for each component. Generic data from WASH-1400, IEEE Std 500, and the LER data summaries on valves, pumps, and diesels were combined with plant-specific failure data to produce "updated" failure information. All the IP2 specialized component hardware failure data, both generic and updated, are contained in Table 1.5.1-4 (IP3 1.6.1-4). This table contains (by system, component, and failure mode) plant-specific data on the number of failures and service hours or demands. For some components, it was determined that specifications of the system was warranted because of its impact on the data values. 

CCPS Generic Failure Rate Data Base... 

Section 5.4 describes the use of the CCPS Generic Failure Rate Data Base. Lastly, Section 5.5 contains tables of data in the Generic Failure Rate Data Base, organized by the numbers used to structure the CCPS Taxonomy. 

SAIC provided much of the data used in this book from its proprietary files of previously analyzed and selected information. Since these data were primarily from the nuclear power industry, a literature search and industry survey described in Chapter 4 were conducted to locate other sources of data specific to the process equipment types in the CCPS Taxonomy. Candidate data resources identified through this effort were reviewed, and the appropriate ones were selected. Applicable failure rate data were extracted from them for the CCPS Generic Failure Rate Data Base. The resources that provided failure information are listed in Table 5.1 with data reference numbers used in the data tables to show where the data originated. 

Note SAIC has selected some data from resources 8.1 through 8.15 to construct its proprietary data files for use in performing PRAs. Relevant data from these files was used to construct the CCPS Generic Failure Rate Data Base. Accordingly, all usable data points contained in the resources used by SAIC may not be in the Data Tables in this book. 

Failure rate data selected for the CCPS Generic Failure Rate Data Base were handled using dBase III Data Management in conjunction with the Computerized Aggregation of Reliability Parameters (CARP) developed by SAIC. CARP, designed to be used by... 

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