April 26, 2023
Journal Article

A sensitivity analysis to predict the neutronics behavior of samples irradiated in the VTR rabbit system

Abstract

A low-order neutronics model is developed to carry out hundreds of simulations efficiently and investigate the neutronics behavior of samples being irradiated in a test reactor setting under different geometrical constraints. The low-order model allowed for simulations that yield the expected neutronics behavior of any irradiated sample in any environment and allows for the calculation of highly accurate spatially averaged statistics and idealized spatial distributions in the neutron flux. Several benchmarks are performed to evaluate the performance and limitations of the low-order model revealing many important findings. The low-order model predicted the LHGR in the EBR-II driver fuel to within 2.34% by only simulating the fuel rod by itself, which served as a validation for the model. Sensitivity studies investigated 3% enriched UO2 and U-10Zr being irradiated in the Versatile Test Reactor rabbit system. The analyses investigated a range of combinations of 15 radii and 5 heights for each sample in the rabbit system. Similar data sets are also provided for irradiations in the Advanced Test Reactor’s B-10 irradiation position, which is a thermal neutron spectrum environment. Generalized fits and fit coefficients are obtained for sample heating, reaction rate densities, and local multiplication rate characteristics, allowing the predictions of the neutronics behavior of the samples based on their geometrical constraints. The analyses and fits laid the groundwork for developing a user-end Multiphysics analysis framework to assist and accelerate irradiation experiment design and optimization.

Published: April 26, 2023

Citation

Weiss A., P. Tsvetkov, J. Hearne, M. Kimber, D.W. Wootan, and S.M. Mcdeavitt. 2023. A sensitivity analysis to predict the neutronics behavior of samples irradiated in the VTR rabbit system. Annals of Nuclear Energy 185. PNNL-SA-184360. doi:10.1016/j.anucene.2023.109708

Research topics