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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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NRC’s hybrid AI workshop coming up
The Nuclear Regulatory Commission will host a hybrid public workshop on September 24 from 9 a.m.-5 p.m. Eastern time to discuss its activities for the safe and secure use of artificial intelligence in NRC-regulated activities.
Richard H. Olsher, Hsiao-Hua Hsu, Wells F. Harvey
Nuclear Science and Engineering | Volume 114 | Number 3 | July 1993 | Pages 219-227
Technical Paper | doi.org/10.13182/NSE93-A24035
Articles are hosted by Taylor and Francis Online.
The MCNP Monte Carlo transport code is used by the Los Alamos National Laboratory Health and Safety Division for a broad spectrum of radiation shielding calculations. One such application involves the determination of skyshine dose for a variety of photon sources. To verify the accuracy of the code, it was benchmarked with the Kansas State University (KSU) photon skyshine experiment of 1977. The KSU experiment for the unshielded source geometry was simulated in great detail to include the contribution of groundshine, in-silo photon scatter, and the effect of spectral degradation in the source capsule. The standard deviation of the KSU experimental data was stated to be 7%, while the statistical uncertainty of the simulation was kept at or under 1%. The results of the simulation agreed closely with the experimental data, generally to within 6%. At distances of under 100 m from the silo, the modeling of the in-silo scatter was crucial to achieving close agreement with the experiment. Specifically, scatter off the top layer of the source cask accounted for ∼12% of the dose at 50 m. At distances >300 m, using the 60Co line spectrum led to a dose overresponse as great as 19% at 700 m. It was necessary to use the actual source spectrum, which includes a Compton tail from photon collisions in the source capsule, to achieve close agreement with experimental data. These results highlight the importance of using Monte Carlo transport techniques to account for the nonideal features of even “simple experiments.”