Calculations of kinetic parameters of LFR with the OpenMC Monte Carlo code
Olivares, Darian Andrés (2025)
Diplomityö
2025
School of Energy Systems, Energiatekniikka
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2025050838459
https://urn.fi/URN:NBN:fi-fe2025050838459
Tiivistelmä
This work investigates the different methods used to analyze the effective delayed neutron fraction, βeff, and the effective mean generation time, Λeff, in the OpenMC code, with a particular focus on Lead-cooled Fast Reactors.
Given the high quality of results, the document centers on the implementation of the Iterated Fission Probability (IFP) method in OpenMC. A detailed examination of the theory behind the method, along with the sources of uncertainty, is provided to improve understanding and optimize the method.
The IFP method is verified and validated by running simulations and comparing their accuracy with experimental data and other commonly used methods for calculating kinetic parameters. These values are computed for a set of fast nuclear facilities that are used as benchmarks by various organizations.
In general terms, the IFP method demonstrates correct behavior for this type of calculation, achieving precise results that agree with benchmarks and other references and showing good adaptation to improvements.
Given the high quality of results, the document centers on the implementation of the Iterated Fission Probability (IFP) method in OpenMC. A detailed examination of the theory behind the method, along with the sources of uncertainty, is provided to improve understanding and optimize the method.
The IFP method is verified and validated by running simulations and comparing their accuracy with experimental data and other commonly used methods for calculating kinetic parameters. These values are computed for a set of fast nuclear facilities that are used as benchmarks by various organizations.
In general terms, the IFP method demonstrates correct behavior for this type of calculation, achieving precise results that agree with benchmarks and other references and showing good adaptation to improvements.