EPJ Web Conf.
Volume 247, 2021PHYSOR2020 – International Conference on Physics of Reactors: Transition to a Scalable Nuclear Future
|Number of page(s)||8|
|Section||Sensitivity & Uncertainty Methods|
|Published online||22 February 2021|
VOID COEFFICIENT SENSITIVITY ANALYSIS FOR THE TRIGA MARK II REACTOR AT L.E.N.A. (UNIPV)
1 Politecnico di Milano; Dept. of Energy, Nuclear Eng. Division, Via La Masa 34, 20156, Milan, Italy
2 LPSC-IN2P3-CNRS; 53 Rue des Martyrs, 38026 Grenoble, France
3 Milano Multiphysics; Polihub, Politecnico di Milano, via Durando 39, 20158 Milano, Italy
4 Institut Laue Langevin; 71 Rue des Martyrs, 38042 Grenoble, France
Published online: 22 February 2021
Sensitivity analysis studies the effect of a change in a given parameter to a response function of the system under investigation. In reactor physics, this usually translates into the study of how cross sections and fission spectrum modifications affect the value of the multiplication factor, the delayed neutron fraction or the void coefficient for example. Generalized Perturbation Theory provides a useful tool for the assessment of adjoint weighed functions such as keff and void coefficient sensitivities. In this work, the capability of SERPENT code to perform sensitivity calculation based on GPT is used to study the TRIGA Mark II research reactor installed at L.E.N.A. of University of Pavia. A general sensitivity analysis to the most important reactor’s cross sections has been performed in order to highlight the biggest reactivity contributions. Two numerically challenging tasks related to GPT calculation have been performed thanks to the relatively quick Monte Carlo approach allowed by this reactor: investigating the linearity of the reactivity injection caused by the flooding of the central channel, and calculating the fuel void coefficient sensitivity to the coolant density.
Key words: SENSITIVITY / PERTURBATION THEORY / MONTECARLO / TRIGA
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Initial download of the metrics may take a while.