Propagação de incertezas em redes Bayesianas através do Método de Monte Carlo e Lógica Fuzzy para aplicação em análises probabilísticas de segurança de centrais nucleares

Abstract

This work investigates the propagation of uncertainties in Bayesian Networks, for the Containment Heat Removal System (CHRS), using a hybrid modeling, containing the Monte Carlo Method and fuzzy logic, for the propagation of events using Boolean logic and the human error of action, respectively. CHRS has the function of cooling the water tank being recirculated through the Containment Spray Recirculation System (CSRS). CSRS starts automatically after a refrigerant loss accident (LOCA) and along with CHRS finds ways to remove heat from the reservoir. The results obtained through the modeling were satisfactory, evidencing the possibility of estimating uncertainties, even with data shortages.