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2024 MCATK Status.

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Název: 2024 MCATK Status.
Autoři: Sweezy, Jeremy, Burke, Tim, Adams, Terry, Bolding, Simon, Giron, Jesse, Long, Alex, Nolen, Steven, Skinner, Corey, Tumulak, Aaron, Zukaitis, Tony, McCartney, Austin, Trahan, Travis
Zdroj: EPJ Nuclear Sciences & Technologies; 2025, Vol. 11, p1-10, 10p
Témata: MONTE Carlo method, PARALLEL programming, LABORATORIES, C++, PYTHON programming language
Korporace: LOS Alamos National Laboratory
Abstrakt: The Monte Carlo Application Toolkit (MCATK) is a C++ component-based Monte Carlo particle transport capability that has been in development by Los Alamos National Laboratory (LANL) since 2008. This paper presents an update on MCATK's current capabilities, focusing on notable advancements made since the previous status reports (T. Adams, S. Nolen, J. Sweezy, A. Zukaitis, J. Campbell, T. Goorley, S. Greene, R. Aulwes, Ann. Nucl. Energy 82, 41 (2015), T.J. Trahan, T.R. Adams, R.T. Aulwes, S.D. Nolen, J.E. Sweezy, C.J. Werner, Monte Carlo Application ToolKit (MCATK): Advances for 2017, in International Conference on Mathematics & Computational Methods Applied to Nuclear Science & Engineering (Jeju, Korea, 2017). Key enhancements include a Python interface, photon physics, expanded geometry modeling options, improved tallies, and a broader selection of source definitions. Additionally, MCATK now offers stochastic system solvers, shared memory parallelism, and GPU acceleration of ray-tracing tallies. These enhancements have significantly expanded MCATK's functionality. [ABSTRACT FROM AUTHOR]
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Databáze: Complementary Index
Popis
Abstrakt:The Monte Carlo Application Toolkit (MCATK) is a C++ component-based Monte Carlo particle transport capability that has been in development by Los Alamos National Laboratory (LANL) since 2008. This paper presents an update on MCATK's current capabilities, focusing on notable advancements made since the previous status reports (T. Adams, S. Nolen, J. Sweezy, A. Zukaitis, J. Campbell, T. Goorley, S. Greene, R. Aulwes, Ann. Nucl. Energy 82, 41 (2015), T.J. Trahan, T.R. Adams, R.T. Aulwes, S.D. Nolen, J.E. Sweezy, C.J. Werner, Monte Carlo Application ToolKit (MCATK): Advances for 2017, in International Conference on Mathematics & Computational Methods Applied to Nuclear Science & Engineering (Jeju, Korea, 2017). Key enhancements include a Python interface, photon physics, expanded geometry modeling options, improved tallies, and a broader selection of source definitions. Additionally, MCATK now offers stochastic system solvers, shared memory parallelism, and GPU acceleration of ray-tracing tallies. These enhancements have significantly expanded MCATK's functionality. [ABSTRACT FROM AUTHOR]
ISSN:24919292
DOI:10.1051/epjn/2025035