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Efficient Approaches to the Treatment of Uncertainty in Satisfying Regulatory Limits

Grabaskas, David

Abstract Details

2012, Doctor of Philosophy, Ohio State University, Nuclear Engineering.

Utilities operating nuclear power plants in the United States are required to demonstrate that their plants comply with the safety requirements set by the U.S. Nuclear Regulatory Commission (NRC). How to show adherence to these limits through the use of computer code surrogates is not always straightforward, and different techniques have been proposed and approved by the regulator. The issue of compliance with regulatory limits is examined by rephrasing the problem in terms of hypothesis testing. By using this more rigorous framework, guidance is proposed to choose techniques to increase the probability of arriving at the correct conclusion of the analysis. The findings of this study show that the most straightforward way to achieve this goal is to reduce the variance of the output result of the computer code experiments.

By analyzing different variance reduction techniques, and different methods of satisfying the NRC’s requirements, recommendations can be made about the best-practices, that would result in a more accurate and precise result. This study began with an investigation into the point estimate of the 0.95-quantile using traditional sampling methods, and new orthogonal designs. From there, new work on how to establish confidence intervals for the outputs of experiments designed using variance reduction techniques was compared to current, regulator-approved methods. Lastly, a more direct interpretation of the regulator’s probability requirement was used, and confidence intervals were established for the probability of exceeding a safety limit. From there, efforts were made at combining methods, in order to take advantage of positive aspects of different techniques.

The results of this analysis show that these variance reduction techniques can provide a more accurate and precise result compared to current methods. This means an increased probability of arriving at the correct conclusion, and a more accurate characterization of the risk associated with events. While several of these methods are asymptotic in nature, which presents potential drawbacks, issues of convergence appear to be outweighed by the reduction in variance, and improvement of the information contained in the results. Using this knowledge, recommendations were made about the applicability of these methods in the field of reactor safety, and about future regulatory limits and their implications.

Tunc Aldemir, PhD (Advisor)
Richard Denning, PhD (Committee Member)
Marvin Nakayama, PhD (Committee Member)
Alper Yilmaz, PhD (Committee Member)
281 p.

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Citations

  • Grabaskas, D. (2012). Efficient Approaches to the Treatment of Uncertainty in Satisfying Regulatory Limits [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1345464067

    APA Style (7th edition)

  • Grabaskas, David. Efficient Approaches to the Treatment of Uncertainty in Satisfying Regulatory Limits. 2012. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1345464067.

    MLA Style (8th edition)

  • Grabaskas, David. "Efficient Approaches to the Treatment of Uncertainty in Satisfying Regulatory Limits." Doctoral dissertation, Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1345464067

    Chicago Manual of Style (17th edition)