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Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
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Biden executive order to facilitate AI data center power
As demand for artificial intelligence and data centers grows, President Biden issued an executive order yesterday aimed to ensure clean-energy power supply for the technology.
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.