Complexity analysis of the MCNP/X code

Andreas van Wijk; Simon Vanmaercke

Complexity analysis of the MCNP/X code

Andreas van Wijk, Simon Vanmaercke

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Abstract

This work analysis the computational complexity of the MCNP/X code. Based on this analysis a number of rules of thumb have been established. Following these rules of thumb, the user of MCNP/X can gain a reasonable amount of computation time. A second aspect studied in this work is Global Variance Reduction: an iterative process to fix a weight window to reduce the global relative error. GVR allows to have a simulation result with a very flat relative error profile, even at places where neutron flux is low.

Original language	English
Awarding Institution	TUD - Delft University of Technology
Supervisors/Advisors	Van den Eynde, Gert, Supervisor
Place of Publication	Delft, Netherlands
Publisher	TU Delft - Delft University of Technology
State	Published - 1 Dec 2010

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N2 - This work analysis the computational complexity of the MCNP/X code. Based on this analysis a number of rules of thumb have been established. Following these rules of thumb, the user of MCNP/X can gain a reasonable amount of computation time. A second aspect studied in this work is Global Variance Reduction: an iterative process to fix a weight window to reduce the global relative error. GVR allows to have a simulation result with a very flat relative error profile, even at places where neutron flux is low.

AB - This work analysis the computational complexity of the MCNP/X code. Based on this analysis a number of rules of thumb have been established. Following these rules of thumb, the user of MCNP/X can gain a reasonable amount of computation time. A second aspect studied in this work is Global Variance Reduction: an iterative process to fix a weight window to reduce the global relative error. GVR allows to have a simulation result with a very flat relative error profile, even at places where neutron flux is low.

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KW - Monte Carlo

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PB - TU Delft - Delft University of Technology

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