Sensitivity and Uncertainty Analysis of BWR Stability

Sammanfattning: Best Estimate codes are used for licensing, but with conservative assumptions. It is claimed that the uncertainties are covered by the conservatism of the calculation. As Nuclear Power Plants are applying for power up-rates and life extension, evaluation of the uncertainties could help improve the performance, while staying below the limit of the safety margins. Given the problem of unstable behavior of Boiling Water Reactors (BWRs), which is known to occur during operation at certain power and flow conditions, it could cause SCRAM and decrease the economic performance of the plant. Performing an uncertainty analysis for BWR stability would give better understating of the phenomenon and it would help to verify and validate (V&V) the codes used to predict the NPP behavior. This thesis reports an uncertainty study of the impact of Thermal-Hydraulic, Neutronic, and Numerical parameters on the prediction of the stability of the BWR within the framework of OECD Ringhals-1 stability benchmark. The time domain code TRACE/PARCS was used in the analysis. This thesis is divided in two parts: Sensitivity study on Numerical Discretization Parameters (Nodalization, Time Step, etc.) and Uncertainty part. A Sensitivity study was done for the Numerical Parameters (Nodalization and Time step). This was done by refining all possible components until obtaining Space-Time Converged Solution, i.e. further refinement doesn’t change the solution. When the space-time converged solution was compared to the initial discretization, a much better solution has been obtained for both the stability measures (Decay Ratio and Frequency) with the space-time converged model. Further on, important Neutronic and Thermal-Hydraulic Parameters were identified and the uncertainty calculation was performed using the Propagation of Input Errors (PIE) methodology. This methodology, also known as the GRS method, has been used because it has been tested and extensively verified by the industry, and because it allows identifying the most influential parameters using the Spearman Rank Correlation.