[en] This report illustrates the practical synthesis of component and system operating experience into reliabilty parameters which are used in probabilistic risk evaluations of gas cooled reactors (GCRs). Component and system reliability parameters have been extracted from over 65 sources of reliability data, which are classified into four groups: (1) gas cooled reactor data, (2) U.S. nuclear and fossil fired data, (3) summarized data, and (4) special reliability analysis estimates. The data from these sources are synthesized into generic failure rate estimates with variability ranges for GCR components and their failure modes. Repair times are also given. Either this synthesized information or the basic reference documents can be used to quantify the component level data inputs to fault trees for the probabilistic evaluation of hypothesized GCR accident sequences. This collection of data supports the DOE-funded Accident Initiation and Progression Analysis

[en] This report presents the results of a project, sponsored by the Electric Power Research Institute (EPRI) and conducted by NUS Corporation, to develop a well-structured framework for systematically incorporating human-system interactions into probabilistic risk assessments (PRAs). The framework consists of seven distinct steps that represent the minimum number of activities that a PRA systems analyst and a human reliability analyst should perform together to produce a description of human interactions that enhances the usefulness and credibility of the study. SHARP provides a structure for: (1) identifying human interactions, (2) stating key assumptions, (3) focusing on key human interactions, (4) describing them in detail, (5) incorporating the influence of human actions on events modeled in PRA studies, (6) quantifying the impacts, and (7) documenting the results. To help the reader to understand the SHARP process, each SHARP step is illustrated by examples. In addition, the application of SHARP is demonstrated by the use of a comprehensive example based on a steam generator tube rupture accident. (author)

[en] The LaSalle comprehensive probabilistic risk assessment (PRA) includes external events and internal events with explicit treatment of human actions during operations, maintenance, and surveillance. It includes common-cause considerations and dependencies covering all support functions. These human sections are included in the same fault trees applicable to both external and internal events. Realism is incorporated into the PRA via measurable values of plant parameters in contrast to license-base values, via real-time behavior of primary containment which provides more realistic operator response intervals, and via actual measurements of operator responses during engineering simulator exercise of plant-specific transient and accident events. Preliminary correlations of operator responses via the HCR measurements method indicate that measured operator unreliabilities are consistently ten to one hundred times lower than best-estimate values used in earlier PRA's. Some operator responses may indicate an unreliability measure of one thousand less than reported estimates of non-performance (omission failures). Measurements of operator response during plant recovery scenarios are currently being correlated for subsequent inclusion via SHARP methods into the LaSalle PRA. These degraded core event scenarios were defined from the PRA dominant transient and accident cut-sets leading to degraded cores with potential fission product release

No abstract available

[en] Probabilistic risk assessment (PRA) methodology has emerged as one of the most promising tools for assessing the impact of human interactions on plant safety and understanding the importance of the man/machine interface. Human interactions were considered to be one of the key elements in the quantification of accident sequences in a PRA. The approach to quantification of human interactions in past PRAs has not been very systematic. The Electric Power Research Institute sponsored the development of SHARP to aid analysts in developing a systematic approach for the evaluation and quantification of human interactions in a PRA. The SHARP process has been extensively peer reviewed and has been adopted by the Institute of Electrical and Electronics Engineers as the basis of a draft guide for the industry. By carrying out a benchmark process, in which SHARP is an essential ingredient, however, it appears possible to assess the strengths and weaknesses of SHARP to aid human reliability analysts in carrying out human reliability analysis as part of a PRA

[en] The paper illustrates the practical synthesis of previous component and system operating experience into the reliability parameters which are used in probabilistic risk evaluations of gas-cooled reactors (GCRs). Component and system reliability operating experience provides the basic input data for quantifying event tree and fault tree models that describe hypothesized reactor accident sequences. It is therefore necessary to collect and review the existing operating experience described in numerous accounts of power plant operations for both the development of detailed accident models and the quantification of their likelihood. It was found that the presently available operating experience includes enough information to provide both the qualitative and quantitative understanding necessary to evaluate the safety of the gas-cooled reactor designs

[en] The US nuclear industry now focuses on improving plant performance in measurable areas such as availability, safety, and operations. Risk assessment and pioneering work in human reliability analysis (HRA) have provided methods to identify and prioritize numerous design improvements. Improvements such as control room design, training, and procedures have contributed positively to plant performance. Human performance is increasingly recognized as a fundamental contributor to safe, economic, and reliable operation. Industry leaders suggest that improved leadership and management are keys to enhanced plant performance. This paper identifies several critical aspects of individual and group behavior that, if managed, could significantly contribute to improved performance. Some existing tools for measuring performance are cited

[en] Many advancements in the methods for treating human interactions in PRA studies have occurred in the last decade. These advancements appear to increase the capability of PRAs to extend beyond just the assessment of the human's importance to safety. However, variations in the application of these advanced models, data, and judgements in recent PRAs make quantitative comparisons among studies extremely difficult. This uncertainty in the analysis diminishes the usefulness of the PRA study for upgrading procedures, enhancing traning, simulator design, technical specification guidance, and for aid in designing the man-machine interface. Hence, there is a need for a framework to guide analysts in incorporating human interactions into the PRA systems analyses so that future users of a PRA study will have a clear understanding of the approaches, models, data, and assumptions which were employed in the initial study. This paper describes the role of the systematic human action reliability procedure (SHARP) in providing a road map through the complex terrain of human reliability that promises to improve the reproducibility of such analysis in the areas of selecting the models, data, representations, and assumptions. Also described is the role that a human cognitive reliability model can have in collecting data from simulators and helping analysts assign human reliability parameters in a PRA study. Use of these systematic approaches to perform or upgrade existing PRAs promises to make PRA studies more useful as risk management tools. (orig.)

[en] Probabilistic Risk Assessment (PRA) is a method of quantifying the frequency of occurrence and the magnitude of the consequences of accidents in systems that contain hazardous materials such as radioactive fission products, and toxic, flammable or explosive chemicals. The frequency and the magnitude of the consequences are the basic elements of any definition or risk, which is often simply expressed as the product of frequency and magnitude, summed over all accident sequences. PRA is now a mature technique that has been used to estimate risk for a number of industrial facilities. In this paper the author gives examples of beneficial uses of PRA

[en] Methods are presented for the treatment of operator actions, developed in the AIPA risk assessment study. Some examples are given of how these methods were applied to the analysis of potential HTGR accidents. Realistic predictions of accident risks required a balanced treatment of both beneficial and detrimental actions and responses of human operators and maintenance crews. Th essential elements of the human factors methodology used in the AIPA study include event tree and fault tree analysis, time-dependent operator response and repair models, a method for quantifying common cause failure probabilities, and synthesis of relevant experience data for use in these models