Identifying high-impact and high-uncertainty parameters in MiniFuel model predictions

Meehan, Nicholas A.; Gorton, Jacob P.; Capps, Nathan A.; Brown, Nicholas R.

doi:10.1016/j.jnucmat.2025.155745

Identifying high-impact and high-uncertainty parameters in MiniFuel model predictions

Journal Article · Tue Mar 11 00:00:00 EDT 2025 · Journal of Nuclear Materials

DOI:https://doi.org/10.1016/j.jnucmat.2025.155745· OSTI ID:3002854

^[1]; ^[2]; Capps, Nathan A. ^[2]; ^[1]

Univ. of Tennessee, Knoxville, TN (United States)
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

The MiniFuel irradiation platform at Oak Ridge National Laboratory's High Flux Isotope Reactor (HFIR) is a flexible, high-throughput separate effects test capability. Finite element thermal models are relied upon to design MiniFuel experiments and to achieve experimental objectives. Recent reports show good agreement in the model prediction of target fuel temperatures, but as the capability of the experiments is extended to higher temperatures, the uncertainty in the model predictions must be quantified. To that end, high-impact, high-uncertainty parameters that contribute the most uncertainty to the model are identified. The uncertainty quantification was accomplished through a series of screening and sensitivity analyses. The first analysis utilizes the method of Morris to perform a computationally efficient preliminary screening that considers uncertainty in a large number of the model inputs. The most important parameters identified in the Morris screening study were then considered in a Sobol sensitivity analysis that more robustly ranks and quantifies the uncertainty associated with each parameter. From these analyses, it was determined that thermal contact conductance between components is the parameter that contributes the highest uncertainty. The estimated uncertainty of the MiniFuel model fuel temperature predictions is ±80 °C in the removable beryllium and ±40 °C in the vertical experiment facilities. In conclusion, the framework established by the series of sensitivity analyses presented herein could easily be adapted to fit the needs of accelerated fuel qualification processes.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Nuclear Energy (NE), Nuclear Fuel Cycle and Supply Chain. Advanced Fuel Campaign

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 3002854

Alternate ID(s):: OSTI ID: 2533589

Journal Information:: Journal of Nuclear Materials, Journal Name: Journal of Nuclear Materials Vol. 609; ISSN 0022-3115

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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