Method for performing real-time probabilistic safety assessments for nuclear power plants

A method for performing real-time probabilistic safety assessments to generate a risk perspective in long-term planning of design and operational changes for nuclear power plants, comprising the steps of:

• a) developing an initial probabilistic safety assessment model for a nuclear power plant, wherein the initial probabilistic safety assessment model is a living AIMS-PSA model developed using existing plant information of a nuclear power plant, plant documentation of said nuclear power plant, and analysts' assumptions in an absence of said existing plant information and plant documentation of said nuclear power plant;
• b) generating a set of probabilistic safety assessment results;
• c) developing a simulation of the nuclear power plant;
• d) measuring real-time parameters from the nuclear power plant;
• e) performing feature extraction on results of the probabilistic safety assessment model combined with corresponding results from the simulation and the measured real-time parameters, wherein extracted features correspond to the measured real-time parameters;
• f) generating a set of system state labels, wherein members of the set of system state labels each comprise an indication of system state function at a unique time;
• g) developing an updated probabilistic safety assessment model using the extracted features and the set of system state labels as training data for a machine learning algorithm;
• and
• h) replacing the initial probabilistic safety assessment model with the updated probabilistic safety assessment model and returning to step b), wherein the updated probabilistic safety assessment model is a living AIMS-PSA model that is used in conjunction with a safety/risk monitor, said safety/risk monitor showing a current risk state based on an actual nuclear power plant configuration and current tests in progress to ensure any needed adjustments are made for continued safe operation of the nuclear power plant.