Validation of Forward Propagation of Uncertainties in Thermal Hydraulic Safety Analysis

In the past few decades, there has been an increasing interest in the use of Best Estimate Plus Uncertainty (BEPU) methodologies for the safety analyses of nuclear reactors. One of the crucial issues is to quantify and propagate the input uncertainties associated to the physical models in the thermal-hydraulic codes. Such a quantification can be performed by comparison with experimental data, and it is usually referred to as Inverse Uncertainty Quantification (IUQ). The OECD/NEA project ATRIUM (Application Tests for Realization of Inverse Uncertainty quantification and validation Methodologies in thermal-hydraulics) aims at performing practical IUQ exercises to bring new insights on the applicability of uncertainty quantifications methods in thermal hydraulic safety analysis. The present work addresses the final Exercise of the project, which involves the propagation of uncertainties in the simulation results of an Intermediate Break Loss-of-Coolant Accident (IBLOCA) in the Hot Leg. The scenario reproduces the conditions of Test 1 conducted at the LSTF facility in Japan, a scaled-down Integral Test Facility (ITF) representing a PWR. The ultimate objective of this thesis is the validation of a RELAP5 model for the simulation of this specific transient scenario. The ultimate objective of this thesis is the validation of a RELAP5 model for the simulation of this specific transient scenario. Exercise 3 of the ATRIUM project is structured in two main phases: the first phase involves the propagation of uncertainties identified in the previous two exercises—specifically related to choked flow and post-CHF modeling—while the second phase builds upon these results to perform the BEPU analysis also including uncertainties associated with boundary and initial conditions. The BEPU analysis is conducted according to Wilks’ formula, propagating uncertainties across 93 simulation cases in addition to the nominal base case. The input variations are generated using the Monte Carlo method. The aim is to estimate the 95th percentile of the selected output variables, as required by the Exercise specifications, with a confidence level of 95%, using the RELAP5 code. The post processing has been carried out by employing Python scripts. The chosen Figures of Merit (FoMs) will be presented in the Results section in the form of percentile plots, to demonstrate the accuracy and robustness of the simulation model. Additionally, the time evolution of key system parameters representing relevant physical phenomena will be analyzed.