A quantitative evaluation of reliability of passive systems within probabilistic safety assessment framework for VHTR

2010 ◽  
Vol 37 (3) ◽  
pp. 345-358 ◽  
Author(s):  
Seok-Jung Han ◽  
Joon-Eon Yang
Author(s):  
Luciano Burgazzi ◽  
Michel Marques

The treatment of passive safety systems within the probabilistic safety assessment models is a difficult and challenging task. The main concern arises from the nature of the passive systems whose predominant operating principles are based on physical phenomena rather than on active components. The present study provides a consistent approach for the integration of passive safety systems into fault tree and event tree based Probabilistic Safety Assessment (PSA) model of accident sequences, in the fashion of and in combination with a front line system or a human action. With reference to the thermal-hydraulic passive systems (e.g. natural circulation systems), in addition to the component failures (i.e. mechanical and electrical faults), the impairment of the physical principle upon which the system relies, deserves special consideration. This makes the relative assessment process different as regards the system model commonly adopted in the fault tree approach (i.e. exponential failure model). For the thermal-hydraulic passive system, since the failure process is driven mainly by the occurrence of the phenomenological failure modes, each pertinent basic event will be characterized by defined critical parameters (e.g. non-condensable fraction) that are expected to drive the failure mechanisms. An application of this approach is presented, with reference to a system designed for decay heat removal of advanced Light Water Reactors, relying on natural circulation and provided with a heat exchanger immersed in a cooling pool, acting as heat sink, and connected to the pressure vessel via steam and condensate lines.


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 929
Author(s):  
Gyun Seob Song ◽  
Man Cheol Kim

Monte Carlo simulations are widely used for uncertainty analysis in the probabilistic safety assessment of nuclear power plants. Despite many advantages, such as its general applicability, a Monte Carlo simulation has inherent limitations as a simulation-based approach. This study provides a mathematical formulation and analytic solutions for the uncertainty analysis in a probabilistic safety assessment (PSA). Starting from the definitions of variables, mathematical equations are derived for synthesizing probability density functions for logical AND, logical OR, and logical OR with rare event approximation of two independent events. The equations can be applied consecutively when there exist more than two events. For fail-to-run failures, the probability density function for the unavailability has the same probability distribution as the probability density function (PDF) for the failure rate under specified conditions. The effectiveness of the analytic solutions is demonstrated by applying them to an example system. The resultant probability density functions are in good agreement with the Monte Carlo simulation results, which are in fact approximations for those from the analytic solutions, with errors less than 12.6%. Important theoretical aspects are examined with the analytic solutions such as the validity of the use of a right-unbounded distribution to describe the uncertainty in the unavailability/probability. The analytic solutions for uncertainty analysis can serve as a basis for all other methods, providing deeper insights into uncertainty analyses in probabilistic safety assessment.


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