SENSITIVITY ANALYSIS OF PWR SPENT FUEL DUE TO MODELLING PARAMETER UNCERTAINTIES USING SURROGATE MODELS

In the BEPU (Best Estimate Plus Uncertainty) framework, uncertainty quantification (UQ) is a requirement to improve confidence and reliability of code predictions. Over the years, a lot of works have been done to quantify uncertainties in code predictions of spent nuclear fuel (SNF) characteristics due to nuclear data uncertainties. The purpose of this study is to quantify the uncertainty in pressurized water reactor (PWR) fuel assembly radiation source terms (isotopic inventory, activity, decay heat, neutron and gamma source) due to uncertainties in modeling parameters. The deterministic code STREAM is used to predict the source terms of a typical PWR fuel assembly following realistic and detailed irradiation history. For the sensitivity analysis (SA) and UQ, surrogate models are developed based on polynomial chaos expansion (PCE) and variance-based global sensitivity indices (i.e., Sobol’ indices) are employed. The global SA identifies the less important uncertain parameters, showing that the number of uncertain input parameters can be reduced. The surrogate model offers a significantly reduced computational burden even with large number of samples required for the SA/UQ of the model response