The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates. In order to evaluate the impact of these two factors on the safety of the plant, the Risk Informed Safety Margin Characterization (RISMC) project aims to provide insight to decision makers through a series of simulations of the plant dynamics for different initial conditions (e.g., probabilistic analysis and uncertainty quantification). This report focuses, in particular, on the impact of power uprate on the safety margin of a boiling water reactor. The case study considered is a loss of off-site power followed by the possible loss of all diesel generators, i.e., a station black-out (SBO) event. Analysis is performed by using a combination of thermo-hydraulic codes and a stochastic analysis tool currently under development at the Idaho National Laboratory, i.e. RAVEN.Starting from an understanding of possible SBO accident sequences for a typical boiling water reactor, we built the input file for the mechanistic thermal-hydraulics code that models system dynamics under SBO conditions. We also interfaced RAVEN with these codes so that it would be possible to run multiple RELAP simulation runs by changing specific portions of the input files. We both employed classical statistical tools, i.e. Monte-Carlo, and more advanced machine learning based algorithms to perform uncertainty quantification in order to quantify changes in system performance and limitations as a consequence of power uprate. We also employed advanced data analysis and visualization tools that helped us to correlate simulation outcomes such as maximum core temperature with a set of input uncertain parameters.Results obtained give a detailed investigation of the issues associated with a plant power uprate including the effects of SBO accident scenarios. We were able to quantify how the timing of specific events was impacted by a higher nominal reactor core power. Such safety insights can provide useful information to the decision makers to perform risk-informed margins management.ii CONTENTS

No abstract

RAVEN is a probability distribution agnostic, code agnostic platform for using Monte Carlo style sampling of stochastic parameters for thermal hydraulics codes for the purposes of a Risk Informed Safety Margin Characterized (RISMC) approach to PRA analysis. RISMC formulation allows for the determination of probabilistic safety margins, defined as the probability that a safety mechanism will be overwhelmed. Standard deterministic safety margins are often characterized as a ratio of the stress on a safety mechanism to its ability to withstand stress. These are most often performed by utilizing a systems thermal hydraulic computer code such as RELAP-7. By integrating RELAP-7 and RAVEN, it has been shown that a large portion of parameter space can be evaluated enabling new, more detailed analysis of transients. In the past, this kind of analysis was prohibitively expensive due to the large computational power needed, but modern high power computational servers have reduced the cost of such computational power to the point that these analyses are cost effective. The proposed project will extend the RISMC approach to the evaluation of the economic costs of plant changes, including design, configuration and operational changes to the cost of the potential consequences of both performing and not performing the changes. Using Probabilistic Risk Assessment (PRA) techniques to evaluate incidents likely to cause economic damage, PRA informed thermal hydraulics modeling can be conducted by applying RAVEN and RELAP-7. This analysis can be used to evaluate the economic viability of various plant upgrades. By combining the analysis of possible system configuration and operational parameters with Level 2 and 3 PRA economic impact data, it will be possible to compare the cost of plant changes with the potential for economic damage from severe accidents both with and without reinforced safety margins. Together these can provide a basis for the economic valuation of safety margins and safety margin upgrades using the RISMC approach.