Radiation Physics and Engineering
A peer-reviewed journal published by K. N. Toosi University of Technology

‎Development of SUAP toolkit for performing uncertainty quantification and sensitivity analysis in fuel performance ‎m‎odeling‎

Document Type : Research Article

Authors

Hamed Khodadadi
Kamyar Sabetghadam

Department of Nuclear Engineering, Faculty of Physics, University of Isfahan‎, ‎Isfahan‎, ‎Iran

https://doi.org/10.22034/rpe.2022.348646.1093
Abstract
Probabilistic uncertainty and sensitivity analysis is frequently recommended for safety and reliability assessment of computer simulations. For this purpose, SUAP has been developed, and its latest version is capable of working on analysis results obtained using five well-known nuclear codes (i.e. FRAPCON, FRAPTRAN, FEMAXI, MCNP, and COBRA). SUAP provides support to properly quantify input uncertainties as to probability distributions and appropriate dependency functions. Using the Monte-Carlo sampling method, random combinations of different uncertain input parameters are generated and used to make input files for the corresponding code applied for the modeling. To quantify uncertainties, SUAP determines the variation range for each specific output parameter at any chosen time and/or location. Moreover, sensitivity analysis is accomplished based on the Spearman correlation. In this study, in order to evaluate SUAP applicability, UQ&SA for fuel performance modeling of VVER-1000 fuel rods using FRAPCON code has been accomplished. Acquired results exhibit the possible range of uncertainties in fuel centerline temperature, as well as the importance of different uncertain input parameters on that.

Highlights

  • Probabilistic uncertainty quantification and sensitivity analysis is  facilitated using SUAP toolkit.
  • SUAP is capable of coupling with some frequently used nuclear codes (FRAPCON, FRAPTRAN, ...).
  • Monte-Carlo sampling method is used.
  • Sensitivity (or importance) analysis using Spearman rank ordered coefficient is studied.
  • There are no limitations neither on the numbers of uncertain input parameters nor on the number of the code runs.

Keywords

Uncertainty Quantification and sensitivity analysis (UQ&SA)
Monte-Carlo sampling
Spearman' s rank-ordered coefficient
Fuel performance analysis
Safety analysis
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Radiation Physics and Engineering
Volume 4, Issue 1
Winter 2023
Pages 53-60

  • Receive Date 23 June 2022
  • Revise Date 06 August 2022
  • Accept Date 15 August 2022

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