Abstract
Within material test reactor calculations, energy dependent flux and reaction rate uncertainties are typically not quantified when performing as-run analyses to determine the neutron field experienced by the experiment. When high fidelity Monte-Carlo codes are used in such analyses, straight forward methods to calculate output uncertainties are not available, instead expert opinion is used to postulate computational uncertainties. New methods to propagate uncertainties through these high fidelity simulations are available when sufficient computational power is available. A tool is developed here for sampling any part of an MCNP input from random distributions to determine output uncertainties based on those inputs. Another tool is developed to sample nuclear data cross-section in ACE format using multi-group nuclear data covariances. The Total Monte-Carlo Method and Gesellschaft für Anlagen-und Reaktorsicherheit method (GRS) are implemented and compared to one another as well as MCNP sensitivity and uncertainty calculations. The methods were applied to the Godiva critical sphere k-eigenvalue, the UAM pin-cell benchmark energy dependent flux and reaction rates, and the Advanced Test Reactor energy dependent flux within an experimental location. The two methods agree well, with GRS allowing for an order of magnitude speedup for reaction rate uncertainty calculations and several orders of magnitude for eigenvalue uncertainty calculations.
Original language | English |
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Article number | 108629 |
Journal | Annals of Nuclear Energy |
Volume | 165 |
DOIs | |
State | Published - Jan 2022 |
Funding
The authors wish to acknowledge that this work was performed by funding from Idaho National Laboratory (INL) by Battelle Energy Alliance, LLC under contract DE-AC07-05ID14517.
Funders | Funder number |
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Battelle Energy Alliance | DE-AC07-05ID14517 |
Idaho National Laboratory |
Keywords
- Material test reactors
- Nuclear data uncertainties
- Uncertainty quantification