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September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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DOE on track to deliver high-burnup SNF to Idaho by 2027
The Department of Energy said it anticipated delivering a research cask of high-burnup spent nuclear fuel from Dominion Energy’s North Anna nuclear power plant in Virginia to Idaho National Laboratory by fall 2027. The planned shipment is part of the High Burnup Dry Storage Research Project being conducted by the DOE with the Electric Power Research Institute.
As preparations continue, the DOE said it is working closely with federal agencies as well as tribal and state governments along potential transportation routes to ensure safety, transparency, and readiness every step of the way.
Watch the DOE’s latest video outlining the project here.
R. J. Sheu, A. Y. Chen, Y.-W. H. Liu, S. H. Jiang
Nuclear Science and Engineering | Volume 159 | Number 1 | May 2008 | Pages 23-36
Technical Paper | doi.org/10.13182/NSE159-23
Articles are hosted by Taylor and Francis Online.
In this study, discrete ordinates and Monte Carlo methods were applied to solve the radiation transport problem for a simplified spent fuel storage cask considering fixed neutron and gamma-ray sources. The results were compared, and the causes for their differences were investigated. In addition, a hybrid method based on the Consistent Adjoint Driven Importance Sampling (CADIS) methodology has been adopted to accelerate the Monte Carlo simulations. CADIS utilizes a deterministic adjoint function for variance reduction through source biasing and consistent transport biasing. The problem encountered and its possible solution for applying the source biasing in such a large volume source are described. Compared with the unbiased case, the computational efficiency is improved by a factor of several tens for neutron transport, and the efficiency is increased tremendously by about five orders of magnitude for gamma-ray transport. It has been demonstrated that the biasing scheme applied here is very effective in the shielding calculations for a spent fuel storage cask using the Monte Carlo method.