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Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Take steps on SNF and HLW disposal
Matt Bowen
With a new administration and Congress, it is time once again to ponder what will happen—if anything—on U.S. spent nuclear fuel and high-level waste management policy over the next few years. One element of the forthcoming discussion seems clear: The executive and legislative branches are eager to talk about recycling commercial SNF. Whatever the merits of doing so, it does not obviate the need for one or more facilities for disposal of remaining long-lived radionuclides. For that reason, making progress on U.S. disposal capabilities remains urgent, lest the associated radionuclide inventories simply be left for future generations to deal with.
In March, Rick Perry, who was secretary of energy during President Trump’s first administration, observed that during his tenure at the Department of Energy it became clear to him that any plan to move SNF “required some practical consent of the receiving state and local community.”1
M. Nowak, D. Mancusi, D. Sciannandrone, E. Masiello, H. Louvin, E. Dumonteil
Nuclear Science and Engineering | Volume 193 | Number 9 | September 2019 | Pages 966-981
Technical Paper | doi.org/10.1080/00295639.2019.1578568
Articles are hosted by Taylor and Francis Online.
In radiation protection studies, the goal is to estimate the response of a detector exposed to a strongly attenuated radiation field. Monte Carlo (MC) particle transport codes give the possibility to efficiently solve for such responses using several variance-reduction (VR) methods that help allocating more CPU time to the simulation of highly contributing histories. The TRIPOLI-4® MC particle transport code offers two main methods, the exponential transform and adaptive multilevel splitting (AMS), which rely on the definition of a suitable importance map. In this paper, we present an implementation of a generalized Consistent Adjoint Driven Importance Sampling (CADIS) methodology for TRIPOLI-4. The implementation relies on coupling with the IDT code, a deterministic solver for the Boltzmann adjoint transport equation, for the generation of importance maps. We study the performance of both VR methods present in TRIPOLI-4 in this setting. In particular, to our knowledge, this is the first time that a CADIS-like methodology has been applied to AMS.
