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  • 1
    Electronic Resource
    Electronic Resource
    350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.
    Risk analysis 25 (2005), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: Safety systems are important components of high-consequence systems that are intended to prevent the unintended operation of the system and thus the potentially significant negative consequences that could result from such an operation. This presentation investigates and illustrates formal procedures for assessing the uncertainty in the probability that a safety system will fail to operate as intended in an accident environment. Probability theory and evidence theory are introduced as possible mathematical structures for the representation of the epistemic uncertainty associated with the performance of safety systems, and a representation of this type is illustrated with a hypothetical safety system involving one weak link and one strong link that is exposed to a high temperature fire environment. Topics considered include (1) the nature of diffuse uncertainty information involving a system and its environment, (2) the conversion of diffuse uncertainty information into the mathematical structures associated with probability theory and evidence theory, and (3) the propagation of these uncertainty structures through a model for a safety system to obtain representations in the context of probability theory and evidence theory of the uncertainty in the probability that the safety system will fail to operate as intended. The results suggest that evidence theory provides a potentially valuable representational tool for the display of the implications of significant epistemic uncertainty in inputs to complex analyses.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Risk analysis 11 (1991), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: The performance of a probabilistic risk assessment (PRA) for a nuclear power plant is a complex undertaking, involving the assembly of an accident frequency analysis, an accident progression analysis, a source term analysis, and a consequence analysis. Each of these analyses is, in itself, quite complex. Uncertainties enter into a PRA from each of these analyses. An important focus in recent PRAs has been to incorporate these uncertainties at each stage of the analysis, propagate the subsequent uncertainties through the entire analysis, and include uncertainty in the final results. Monte Carlo procedures based on Latin hypercube sampling provide one way to perform propagations of this type. In this paper, the results of two complete and independent Monte Carlo calculations for a recently completed PRA for a nuclear power plant are compared as a means of providing empirical evidence on the repeatability of uncertainty and sensitivity analyses for large-scale PRA calculations. These calculations use the same variables and analysis structure with two independently generated Latin hypercube samples. The results of the two calculations show a high degree of repeatability for the analysis of a very complex system.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Risk analysis 8 (1988), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: Many different techniques have been proposed for performing uncertainty and sensitivity analyses on computer models for complex processes. The objective of the present study is to investigate the applicability of three widely used techniques to three computer models having large uncertainties and varying degrees of complexity in order to highlight some of the problem areas that must be addressed in actual applications. The following approaches to uncertainty and sensitivity analysis are considered: (1) response surface methodology based on input determined from a fractional factorial design; (2) Latin hypercube sampling with and without regression analysis; and (3) differential analysis. These techniques are investigated with respect to (1) ease of implementation, (2) flexibility, (3) estimation of the cumulative distribution function of the output, and (4) adaptability to different methods of sensitivity analysis. With respect to these criteria, the technique using Latin hypercube sampling and regression analysis had the best overall performance. The models used in the investigation are well documented, thus making it possible for researchers to make comparisons of other techniques with the results in this study.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Risk analysis 10 (1990), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: The individual plant analyses in the U.S. Nuclear Regulatory Commission's reassessment of the risk from commercial nuclear power plants (NUREG-1150) consist of four parts: systems analysis, accident-progression analysis, source-term analysis, and consequence analysis. Careful definition of the interfaces between these parts is necessary for both information flow and computational efficiency. This paper describes the procedure used to define the interface between the source-term analysis and the consequence analysis. This interface is accomplished by forming groups of source terms with similar properties and then performing one set of MACCS calculations for each group.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Risk analysis 14 (1994), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: When viewed at a high level, performance assessments (PAs) for complex systems involve two types of uncertainty: stochastic uncertainty, which arises because the system under study can behave in many different ways, and subjective uncertainty, which arises from a lack of knowledge about quantities required within the computational implementation of the PA. Stochastic uncertainty is typically incorporated into a PA with an experimental design based on importance sampling and leads to the final results of the PA being expressed as a complementary cumulative distribution function (CCDF). Subjective uncertainty is usually treated with Monte Carlo techniques and leads to a distribution of CCDFs. This presentation discusses the use of the Kaplan/Garrick ordered triple representation for risk in maintaining a distinction between stochastic and subjective uncertainty in PAs for complex systems. The topics discussed include (1) the definition of scenarios and the calculation of scenario probabilities and consequences, (2) the separation of subjective and stochastic uncertainties, (3) the construction of CCDFs required in comparisons with regulatory standards (e.g., 40 CFR Part 191, Subpart B for the disposal of radioactive waste), and (4) the performance of uncertainty and sensitivity studies. Results obtained in a preliminary PA for the Waste Isolation Pilot Plant, an uncertainty and sensitivity analysis of the MACCS reactor accident consequence analysis model, and the NUREG-1150 probabilistic risk assessments are used for illustration.
    Type of Medium: Electronic Resource
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