Abstract
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.
Original language | English |
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Title of host publication | Proceedings of the 2018 International Congress on Advances in Nuclear Power Plants, ICAPP 2018 |
Publisher | American Nuclear Society |
Pages | 1080-1084 |
Number of pages | 5 |
ISBN (Electronic) | 9780894487552 |
State | Published - 2018 |
Event | 2018 International Congress on Advances in Nuclear Power Plants, ICAPP 2018 - Charlotte, United States Duration: Apr 8 2018 → Apr 11 2018 |
Publication series
Name | Proceedings of the 2018 International Congress on Advances in Nuclear Power Plants, ICAPP 2018 |
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Conference
Conference | 2018 International Congress on Advances in Nuclear Power Plants, ICAPP 2018 |
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Country/Territory | United States |
City | Charlotte |
Period | 04/8/18 → 04/11/18 |
Funding
This material is based upon work supported by a Department of Energy Nuclear Energy University Programs Graduate Fellowship. Research partially sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. 1Notice: This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).