scholarly journals Application of Dynamic Probabilistic Safety Assessment Approach for Accident Sequence Precursor Analysis: Case Study for Steam Generator Tube Rupture

2017 ◽  
Vol 49 (2) ◽  
pp. 306-312 ◽  
Author(s):  
Hansul Lee ◽  
Taewan Kim ◽  
Gyunyoung Heo
Keyword(s):  
Steam Generator ◽  
Safety Assessment ◽  
Steam Generator Tube ◽  
Probabilistic Safety Assessment ◽  
Assessment Approach ◽  
Probabilistic Safety

ADS-B: Probabilistic Safety Assessment

2017 ◽  
Vol 70 (4) ◽  
pp. 887-906 ◽  
Author(s):  
Busyairah Syd Ali ◽  
Washington Yotto Ochieng ◽  
Arnab Majumdar
Keyword(s):  
Safety Assessment ◽  
Failure Modes ◽  
Fault Tree Analysis ◽  
Performance Standards ◽  
System Safety ◽  
Probabilistic Safety Assessment ◽  
Assessment Approach ◽  
Primary Means ◽  
Importance Analysis ◽  
Probabilistic Safety

In the effort to quantify Automatic Dependent Surveillance Broadcast (ADS-B) system safety, the authors have identified potential ADS-B failure modes in Syd Ali et al. (2014). Based on the findings, six potential hazards of ADS-B are identified in this paper. The authors then applied the Probabilistic Safety Assessment approach which includes Fault Tree Analysis (FTA) and Importance Analysis methods to quantify the system safety. FTA is applied to measure ADS-B system availability for each identified hazard while Importance Analysis is conducted to identify the most significant failure modes that may lead to the occurrence of the hazards. In addition, risk significance and safety significance of each failure mode are also identified. The result shows that the availability for the ADS-B system as a sole surveillance means is low at 0·898 in comparison to the availability of ADS-B system as supplemental or as primary means of surveillance at 0·95 and 0·999 respectively. The latter availability values are obtained from Minimum Aviation System Performance Standards (MASPS) for Automatic Dependent Surveillance-Broadcast (DO-242A).

scholarly journals Mathematical Formulation and Analytic Solutions for Uncertainty Analysis in Probabilistic Safety Assessment of Nuclear Power Plants

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 929
Author(s):  
Gyun Seob Song ◽  
Man Cheol Kim
Keyword(s):  
Monte Carlo ◽  
Uncertainty Analysis ◽  
Probability Density ◽  
Nuclear Power ◽  
Safety Assessment ◽  
Power Plants ◽  
Mathematical Formulation ◽  
Analytic Solutions ◽  
Probabilistic Safety Assessment ◽  
Probabilistic Safety

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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