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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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ANS continues to expand its certificate offerings
It’s almost been a full year since the American Nuclear Society held its inaugural section of Nuclear 101, a comprehensive certificate course on the basics of the nuclear field. Offered at the 2024 ANS Winter Conference and Expo, that first sold-out course marked a massive milestone in the Society’s expanding work in professional development and certification.
Christopher R. Greulich, James Baciak (Univ of Florida), Kaushik Banerjee, Stylianos Chatzidakis (ORNL)
Proceedings | 2018 International Congress on Advances in Nuclear Power Plants (ICAPP 2018) | Charlotte, NC, April 8-11, 2018 | Pages 1080-1084
A cosmic ray Muon Flexible Framework for Spectral Generation for Monte Carlo Applications (MUFFSgenMC) has been developed to support state-of-the-art cosmic ray muon detection and tomographic applications. The flexible framework allows for easy, fast creation of source terms for popular Monte Carlo applications such as GEANT4 and MCNP, simplifying the process of simulations. The flexible framework contains a variety of analytical, numerical, and parametric models that capture the main characteristics of the muon energy and angular distributions in the range 0 to 90 and at arbitrary energies. The primary model for muon energy distribution is an implementation of the Smith and Duller phenomenological model. The predictions for muon energies in ranging from 1 GeV to 1 TeV and zenith angles 0 to 90 are validated against an extensive series of experimental spectrum measurements. Finally, the open source code available on Matlab’s Mathworks File Exchange (https://www.mathworks.com/ matlabcentral/fileexchange/65585-muffsgenmc) was written to allow users to easily modify and expand the code. MUFFSgenMC can facilitate the study of cosmic ray muons for nuclear nonproliferation applications and will enable development of new muon-based detection and imaging techniques by providing an easy source term generator. 1