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Fuel Cycle & Waste Management
Devoted to all aspects of the nuclear fuel cycle including waste management, worldwide. Division specific areas of interest and involvement include uranium conversion and enrichment; fuel fabrication, management (in-core and ex-core) and recycle; transportation; safeguards; high-level, low-level and mixed waste management and disposal; public policy and program management; decontamination and decommissioning environmental restoration; and excess weapons materials disposition.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
College students help develop waste-measuring device at Hanford
A partnership between Washington River Protection Solutions (WRPS) and Washington State University has resulted in the development of a device to measure radioactive and chemical tank waste at the Hanford Site. WRPS is the contractor at Hanford for the Department of Energy’s Office of Environmental Management.
Kirk Mathews, James Dishaw, Nicholas Wager, Nicholas Prins
Nuclear Science and Engineering | Volume 163 | Number 3 | November 2009 | Pages 191-214
Technical Paper | doi.org/10.13182/NSE163-191
Articles are hosted by Taylor and Francis Online.
Our partial-current-transport (PCT) approach uses the partial currents through the faces of cells in a spatial grid as the unknowns in a linear algebra problem. Emission and externally incident currents are the knowns. The coefficient matrix is determined by boundary conditions and transport within cells. Adaptive PCT models include within-cell flux-distribution parameters that are found by distribution iteration (DI). Upon convergence, scalar fluxes are computed. We develop the approach in general and derive (in slab geometry) a fixed-coefficient PCT diffusion method and an adaptive PCT discrete ordinates method. A parallelized direct solver is used for the large but very sparse linear algebra problem that couples all the cells. Matrix inversion is used for the dense but small within-cell problems. These direct solvers eliminate scattering source iteration (SI). Though requiring more storage, much or most of the computational effort is pleasingly parallel, making the method attractive for large parallel machines with large memories. In comparing our slab geometry implementation with PARTISN, we observed that DI used as many or fewer iterations than SI and succeeded where SI failed, whether alone or with diffusion synthetic acceleration or transport synthetic acceleration. We conclude that DI for adaptive PCT holds great promise as an alternative to SI and its accelerators.