An approach for developing a computer-based aid to assist in monitoring and assessing nuclear power plant status during situations requiring emergency response has been developed. It is based on the representation of regulatory requirements and plant-specific systems and instrumentation in the form of hierarchical rules. Making use of inferencing techniques from the field of artificial intelligence, the rules are combined with dynamic state data to determine appropriate emergency response actions. In a joint project with Portland General Electric Company, a prototype system, called EM-CLASS, was been created to demonstrate the knowledge-based approach for use at the Trojan Nuclear Power Plant. The knowledge domain selected for implementation addresses the emergency classification process chat is used to communicate the severity of the emergency and the extent of response actions required. EM-CLASS was developed using Personal Consultant Plus (PCPlus), a knowledge-based system development shell from Texas Instruments which runs on IBM-PC compatible computers. The knowledge base in EM-CLASS contains over 200 rules. The regulatory basis, as defined in 10 CFR 50, calls for categorization of emergencies into four emergency action level classes: (1) notification of unusual event, (2) alert, (3) site area emergency, and (4) general emergency. Each class is broadly defined by expected frequency and the potential for release of radioactive materials to the environment. In a functional sense, however, each class must be ultimately defined by a complex combination of in- plant conditions, plant instrumentation and sensors, and radiation monitoring information from stations located both on- and off-site. The complexity of this classification process and the importance of accurate and timely classification in emergency response make this particular application amenable to an automated, knowledge-based approach. EM-CLASS has been tested with a simulation of a 1988 Trojan Nuclear Power Plant emergency exercise and was found to produce accurate classification of the emergency using manual entry of the data into the program. / Graduation date: 1997

Nuclear safety is the main concern for the licensing of nuclear power plants, not only in the Republic of South Africa but also worldwide. The design of the nuclear power plant plays an important role in the licensing process, which includes probabilistic and deterministic analysis of a set of design or Licensing basis events. This study was about the deterministic analysis for the sensitivity of licensing basis events radiological consequences to different radiological pathways. The study was done for the Pebble Bed Modular Reactor (PBMR), which is a nuclear power plant, still in its early phase of design approaching its detailed design phase. An abnormal event or an accident could lead to a release of radioactive particles and gases from a Pebble Bed Modular Reactor and could give rise to radiation exposure to workers and the surrounding population. Therefore nuclear events due to PBMR, which are Licensing Basis Events or Design Basis Accidents, must be analysed in order to demonstrate that accidental and routine releases of radioactivity are kept As Low As Reasonably Achievable (ALARA) and that the design basis meets offsite dose requirements with adequate safety margins. In this work, it is also shown that collectively the risk criteria are satisfied in the fundamental safety requirements of National Nuclear Regulator (NNR) of the Republic of South Africa (RSA) and similar risk criteria of the other countries in which it has to be employed. Furthermore the various pathways through which radioactivity can reach the public are analysed. The focus of the study was to determine which pathways deliver the greatest radiation exposure if there is an accident due to an event happening in PBMR and also to provide a LBE analysis process as a step in confirming that the design meets the licensing requirements. / Thesis (M.Sc. ARST) North-West University, 2004

How people perceive risk or threats is important to many disciplines that seek to assist policy makers in developing policies, regulations and laws. Using the previous work of Slovic et al. (Fischhoff, Slovic, Lichtenstein, Read and Combs, 2000; Slovic P., 1992; Slovic, Fischhoff, and Lichtenstein, 2000) in development of the psychometric paradigm, a sample of residents (n=600) from a region with a large number of nuclear reactors was surveyed. The question set was expanded to include demographic questions to determine if they impact risk perception. Two aspects of risk perception were examined, perception of overall risk and perception of riskiness along specific dimensions of concern identified previously in the literature. For both risk and riskiness, respondents’ perceptions of nuclear power were compared to three other perceptions of technologies including use of modern farming methods using chemicals, railroad transportation and coal-generated electricity. The recent increase in public concern about nuclear power following the meltdowns at the Fukushima Dai-ichi nuclear power plant led to the expectation that nuclear power would be rated higher in overall risk and riskiness than the other three technologies consistent with Slovic’s earlier work on risk perception. This expectation was generally supported although respondents tended to perceive modern farming methods using chemical as similar in overall risk and riskiness to nuclear power. The research specifically tested five hypotheses concerning the impact of five demographic factors: gender, race, income, education and political orientation on the overall perception of risk and riskiness. Subsequent analysis using analysis of variance and linear regression found that select demographics only explained 2% of the risk perception for nuclear power generation.

The electric utility companies that own and/or operate the nation’s 112 licensed commercial nuclear power reactors are required by federal law to provide emergency information to residents living around those plants in advance of a nuclear plant emergency. This requires the owner/operators to acknowledge certain risks (e.g., radiation, nuclear plant accidents, evacuation, etc.) that face people living near nuclear generating plants. This dissertation critiques the effectiveness of pre-emergency risk communication strategies by nuclear utilities. Specifically, the dissertation demonstrates that certain historic message themes about nuclear power- termed the "nuclear ethic" -have become embedded in the rhetoric of current nuclear risk communication programs and downplay or mask the seriousness of nuclear plant emergencies, thereby contributing to the apparent ineffectiveness of these communication programs. For example, a survey of residents living around four nuclear plants who receive utility risk communication materials found that nearly two-thirds said they would not follow official instructions in a nuclear plant emergency. Such promotional rhetoric and images remain a part of nuclear risk communication programs because agencies which regulate nuclear power delegate their responsibility for pre-emergency risk communication to the utilities operating the plants. Moreover, there is little involvement in pre-emergency nuclear risk communication by state and local governments. This suggests that risk communication serves a latent symbolic role rather than a functional role for both the regulatory agencies and the utilities by making both groups appear to be isomorphic with societal goals of safety and security for a risky technology. The dissertation concludes by suggesting federal regulatory agencies, and specifically the Federal Emergency Management Agency, intensify their vigilance of risk communication planning and take steps to create authentic two-way communication between the nuclear utilities and the public living near the plants. One way this could be done is by establishing local citizens advisory committees to assess utility risk communication programs and suggest improvements that would help bridge the gap between the nuclear industry’s view of nuclear plant risk and that of the public. / Ph. D.