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Identification of performance indicators for nuclear power plants

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dc.contributor.advisor M.W. Golay and K.F. Hansen. en_US Sui, Yu, 1973- en_US
dc.contributor.other Massachusetts Institute of Technology. Dept. of Nuclear Engineering. en_US 2006-03-24T18:10:18Z 2006-03-24T18:10:18Z 2001 en_US 2001 en_US
dc.description Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering, 2001. en_US
dc.description Includes bibliographical references (p. 160-162). en_US
dc.description.abstract Performance indicators have been assuming an increasingly important role in the nuclear industry. An integrated methodology is proposed in this research for the identification and validation of performance indicators for assessing and predicting nuclear power plant overall performance (i.e., both economic and safety performance) in a systematic and quantitative way. The methodology consists of four steps: the selection of target sites/plants, the identification and refinement of candidate indicators, the collection of historical operating records of selected indicators, and the identification and evaluation of correlations between selected indicators and plant performance through data analysis. The methodology is centered upon individual plants, using plant-specific operation records to identify and validate plant-specific correlations. It can also be applied to multiple plants and the results from different plants can be compared to identify and analyze commonalities and differences in plant operations across-plant. Case studies of the proposed methodology were performed at three target plants. A list of candidate performance indicators was identified through a sensitivity analysis on a quantitative model of nuclear power plant operation. The list was validated and supplemented through interviews with plant personnel and a refined, plant-specific list was obtained for each target plant. Historical operating records of candidate indicators in the lists were collected from target plants. Data analyses, including correlational analysis, multivariate regression analysis, and lead/lag time analysis, were performed using the historical data collected. en_US
dc.description.abstract (cont.) The methodology was originally intended for the identification of leading indicators, which can provide advance warnings of deterioration of performance before the direct outcome indicators are affected. A regression-based lead/lag time analysis method was proposed and applied in the case studies to evaluate lead/lag relationships between candidate indicators and plant performance. However, the method did not produce stable and reliable results by using the data currently available at the target plants and was not able to identify leading indicators with certainty. As a result, we shifted the focus of our data analysis to identifying correlations between candidate indicators and plant performance through correlational analysis and multivariate regression analysis. Several findings are noteworthy: (1) Data analysis results were sensitive to the indicators and data points used, mainly due to the small number of data points (30-60) available for use in the analyses; (2) Data analysis results generally agreed with our knowledge and expectation, with a few exceptions; (3) Correlations showed large variations from plant to plant; (4) Correlations varied from time to time at most target plants; (5) The outcome indicators with smoother patterns (e.g., the INPO performance index) tended to correlate better with candidate indicators than the outcome indicators that measured relatively rare events and had sharp changes in their patterns (e.g., unplanned capability loss factor); (6) Work order backlogs stood out as important indicators for all three target plants; ... en_US
dc.description.statementofresponsibility by Yu Sui. en_US
dc.format.extent 175 p. en_US
dc.format.extent 6941876 bytes
dc.format.extent 6941683 bytes
dc.format.mimetype application/pdf
dc.format.mimetype application/pdf
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.subject Nuclear Engineering. en_US
dc.title Identification of performance indicators for nuclear power plants en_US
dc.type Thesis en_US Ph.D. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Nuclear Engineering. en_US
dc.identifier.oclc 55001302 en_US

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