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Mathematics & Computation
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.
Meeting Spotlight
International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025)
April 27–30, 2025
Denver, CO|The Westin Denver Downtown
Standards Program
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
Dragonfly, a Pu-fueled drone heading to Titan, gets key NASA approval
Curiosity landed on Mars sporting a radioisotope thermoelectric generator (RTG) in 2012, and a second NASA rover, Perseverance, landed in 2021. Both are still rolling across the red planet in the name of science. Another exploratory craft with a similar plutonium-238–fueled RTG but a very different mission—to fly between multiple test sites on Titan, Saturn’s largest moon—recently got one step closer to deployment.
On April 25, NASA and the Johns Hopkins University Applied Physics Laboratory (APL) announced that the Dragonfly mission to Saturn’s icy moon passed its critical design review. “Passing this mission milestone means that Dragonfly’s mission design, fabrication, integration, and test plans are all approved, and the mission can now turn its attention to the construction of the spacecraft itself,” according to NASA.
F. Bostelmann, S. E. Skutnik, E. D. Walker, G. Ilas, W. A. Wieselquist
Nuclear Technology | Volume 208 | Number 4 | April 2022 | Pages 603-624
Technical Paper | doi.org/10.1080/00295450.2021.1943122
Articles are hosted by Taylor and Francis Online.
A SCALE model was developed for the Molten Salt Reactor Experiment (MSRE) benchmark that was recently added to the International Handbook of Evaluated Reactor Physics Benchmark Experiments. This SCALE model served as a basis for criticality calculations and nuclear data sensitivity and uncertainty analyses with the Monte Carlo code Shift and the TSUNAMI computational capabilities in the SCALE code system. The focus of this work is the assessment of the impact of nuclear data on the calculated eigenvalue results in support of the discussion of differences between the calculated and the experimental eigenvalue result.
The differences in the eigenvalues obtained using the ENDF/B-VII.0, ENDF/B-VII.1, and ENDF/B-VIII.0 nuclear data libraries cover a relatively small range of 230 pcm. Since eigenvalue sensitivity of the MSRE is dominated by the neutron multiplicity and neutron capture of 235U and elastic scattering in graphite, relevant changes in the ENDF/B libraries for nuclear reactions (such as carbon capture) that caused large differences in other graphite-moderated systems did not have a significant impact. Propagation of nuclear data uncertainty results in an eigenvalue uncertainty of pcm with the major contributors being U neutron multiplicity, graphite elastic scattering, and 7Li neutron capture.
All calculations resulted in large differences of 2000 pcm in eigenvalue compared to the benchmark experimental value. Several potential contributors to this difference—including uncertainties and gaps in the knowledge of the material, geometry, and nuclear data—were identified.
Simplified models of the full MSRE core were developed, and similarity assessments were conduced with the full MSRE core model. It was found that simplified models can serve as adequate surrogates of the full-core model such that they can be used for performing selected nuclear data performance assessments with a lower computational burden.