The intent of this book is to present a comprehensive review of a sensitivity-based methodology developed to utilize differential and integral information in the estimation of reactor performance parameters and their associated uncertainties. It is generally recognized that uncertainties in calculated reactor design parameters such as breeding ratio, power distribution, reactivity worth, etc. may necessitate excessive and expensive design margins. For example, adequate design margins are required to account for uncertainties in the predicted peak thermal power which affects fuel and cladding temperatures, and fluence-induced creep and swelling in structural materials. Additional design margins are included to account for uncertainties in required enrichment. Excess reactivity results in increased control requirements while underprediction of enrichment would require limiting operating conditions. Thus, the establishment of a systematic approach for quantifying these uncertainties and assessing their principal components is a necessary step before a significant reduction in these uncertainties, and the associated design margins, can be achieved. The necessary complex techniques now have become fairly well developed and deserve a comprehensive review and evaluation of the type presented here.
KeywordsNuclear Data Sensitivity Theory Design Margin Benchmark Measurement Limit Operating Condition
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- 1.Ombrellaro, P. A., Bennett, R. A., Daughtry, J. W., Dobbin, R. D., Harris, R. A., Nelson, J. V., Peterson, R. E. and Rathrock, R. B., “Biases for Current FFTF Calculational Methods,” Proceedings of American Nuclear Society Topical Meeting on Advances in Reactor Physics, Gatlinburg, Tennessee, edited by E. G. Silver, April 10–12, 1978.Google Scholar
- 2.Doncals, R. A., Lake, J. A. and Paik, N. C., “Use of Integral Data in the Development of Design Methods for Fast Reactors,” Proceedings of American Nuclear Society Topical Meeting on Advances in Reactor Physics, Gatlinburg, Tennessee, edited by E. G. Silver, April 10–12, 1978.Google Scholar
- 3.Hammer, P., “Nuclear Data Needs for Pu Breeders,” International Conference on Nuclear Cross-Sections for Technology, Knoxville, Tennessee, October 22–26, 1979.Google Scholar
- 4.Pazy, A., Rakavy, G., Reiss, I., Wagschal, J. J., Ya’ari, Atara and Yeivin, Y., “The Role of Integral Data in Neutron Cross-Section Evaluation,” Nuclear Science Engineering, 55, Pages 280–295, 1974.Google Scholar
- 5.Weisbin, C. R., Oblow, E. M., Marable, J. H. and Salvatores, M., “Data Adjustment: A Cautiously Optimistic View for the Improvement of Design Performance Calculations and Data Assessment,” Transactions American Nuclear Society, 27, Page 881, 1977.Google Scholar
- 6.Paik, N. C., “Significance of Nuclear Data on the Development of the LMFBR Industry,” National Bureau of Standards Special Publication 425, Page 39, 1975.Google Scholar