Isotopic Analysis of High-Burnup PWR Spent Fuel Samples From the Takahama-3 Reactor (NUREG/CR-6798)

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Publication Information

Manuscript Completed: May 2002
Date Published: January 2003

Prepared by:
C. E. Sanders, L C. Gauld

Oak Ridge National Laboratory
Managed by UT-Battelle, LLC
Oak Ridge, TN 37831-6370

R. Y. Lee, NRC Project Manager

NRC Job Code W6479

Prepared for:
Division of Systems Analysis and Regulatory Effectiveness
Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington, DC 20555-0001

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Abstract

This report presents the results of computer code benchmark simulations against spent fuel radiochemical assay measurements from the Kansai Electric Ltd. Takahama-3 reactor published by the Japan Atomic Energy Research Institute. Takahama-3 is a pressurized-water reactor that operates with a 17 x 17 fuel-assembly design. Spent fuel samples were obtained from assemblies operated for 2 and 3 cycles and achieved a maximum burnup of 47 GWd/MTU. Radiochemical analyses were performed on two rods having an initial enrichment of 4.11 wt %, and one integral burnable absorber rod containing Gd2O3. These measurements represent the highest enrichment and highest burnup samples currently available in the United States. The benchmark results are important to burnup credit initiatives in the United States since the lack of available benchmark data has led to restrictions on the allowable credit beyond 4.0 wt % and 40 GWd/MTU. Although the primary objective of the measurements was support of burnup credit, radiochemical analyses were also available for a number of actinide and fission product nuclides important to decay heat and radiation source term analysis. Isotopic predictions from. both the SCALE 4.4a and HELIOS–I.6 code systems were used in this benchmark study. The results indicate that the level of agreement between predictions and measurements is very good. The results, for the most part, are consistent with the findings of earlier studies for lower enrichment and lower burnup samples and yield sinilar biases and levels of uncertainty.

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