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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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PR: American Nuclear Society welcomes Senate confirmation of Ted Garrish as the DOE’s nuclear energy secretary
Washington, D.C. — The American Nuclear Society (ANS) applauds the U.S. Senate's confirmation of Theodore “Ted” Garrish as Assistant Secretary for Nuclear Energy at the U.S. Department of Energy (DOE).
“On behalf of over 11,000 professionals in the fields of nuclear science and technology, the American Nuclear Society congratulates Mr. Garrish on being confirmed by the Senate to once again lead the DOE Office of Nuclear Energy,” said ANS President H.M. "Hash" Hashemian.
Luka Snoj, Ivan Kodeli, Igor Remec
Nuclear Science and Engineering | Volume 178 | Number 4 | December 2014 | Pages 496-508
Technical Paper | doi.org/10.13182/NSE14-30
Articles are hosted by Taylor and Francis Online.
A complete evaluation of the experimental uncertainties of the KRITZ-2 series of critical and relative fission rate experiments was performed within the International Reactor Physics Experiment Evaluation Project. The uncertainties in the benchmark model keff are mainly due to uranium enrichment, plutonium content [mixed oxide (MOX) fuel], pitch, and boron isotopic composition. The largest contribution to the uncertainty in the benchmark model keff is from the uncertainty in the bias due to the homogenization of the particulate MOX fuel. In addition, uncertainties due to nuclear data libraries are presented. The keff's calculated with various nuclear data libraries systematically underpredict the benchmark model keff by one to three times the standard experimental uncertainties. When taking into account uncertainties in nuclear data estimated using SCALE-6.0 and JENDL-4.0m covariances, the benchmark and calculated keff's agree within 1σ of the total—experimental plus calculational—uncertainties. In contrast to the criticality benchmark data, the calculated relative fission rates agree very well with the experimental ones, especially when eliminating systematic errors due to normalization.