scholarly journals New trends in Multihazards Probabilistic Safety Assessment for nuclear installations: the H2020-NARSIS Project

2020 ◽  
Author(s):  
Evelyne Foerster ◽  
Behrooz Bazargan-Sabet ◽  
James Daniell ◽  
Pierre Gehl ◽  
Philip J. Vardon ◽  
...  
Keyword(s):  
Nuclear Power ◽  
Safety Assessment ◽  
Power Plants ◽  
Severe Accident ◽  
Management Decision ◽  
Nuclear Facilities ◽  
Probabilistic Safety Assessment ◽  
Human Aspects ◽  
Support Organizations ◽  
Probabilistic Safety

<p>The methodology for Probabilistic Safety Assessment (PSA) of Nuclear Power Plants (NPPs) has been used for decades by practitioners to better understand the most probable initiators of nuclear accidents by identifying potential accident scenarios, their consequences, and their probabilities. However, despite the remarkable reliability of the methodology, the Fukushima Dai-ichi nuclear accident in Japan, which occurred in March 2011, highlighted a number of challenging issues (e.g. cascading event - cliff edge - scenarios) with respect to the application of PSA questioning the relevance of PSA practice, for such low-probability but high-consequences external events. Following the Fukushima Dai-ichi accident, several initiatives at the international level, have been launched in order to review current practices and identify shortcomings in scientific and technical approaches for the characterization of external natural extreme events and the evaluation of their consequences on the safety of nuclear facilities.</p><p>The H2020 project “New Approach to Reactor Safety ImprovementS” (NARSIS, 2017-2021) aims at proposing some improvements to be integrated in existing PSA procedures for NPPs, considering single, cascade and combined external natural hazards (earthquakes, flooding, extreme weather, tsunamis). It coordinates the research efforts of eighteen partners encompassing leading universities, research institutes, technical support organizations (TSO), nuclear power producers and suppliers, reactor designers and operators from ten countries.</p><p>The project will lead to the release of various tools together with recommendations and guidelines for use in nuclear safety assessment, including a Bayesian-based multi-risk framework able to account for causes and consequences of technical, social/organizational and human aspects and as well as a supporting Severe Accident Management decision-making tool for demonstration purposes.</p><p>The NARSIS project has now been running for two years and a half, and the first set of deliverables and tools have been produced as part of the effort of the consortium. Datasets have been collected, methodologies tested, states of the art have been produced, and various criteria and plans developed. First results have started to emerge and will be presented here.</p>

Progression of Severe Accidents, Containment Performance, and Estimates of Releases of Radionuclides-Level-2 Probabilistic Safety Assessment IPHWR

2017 ◽  
Vol 3 (2) ◽  
Author(s):  
Rajee Guptan ◽  
A. K. Vijaya ◽  
Vibha Hari ◽  
Rajeev Nama
Keyword(s):  
Nuclear Power ◽  
Safety Assessment ◽  
Power Plants ◽  
Severe Accident ◽  
Probabilistic Safety Assessment ◽  
Loss Of Coolant Accident ◽  
Level 1 ◽  
Level 2 ◽  
Probabilistic Safety

Probabilistic safety assessment (PSA) of nuclear power plants is performed to yield insights into the safety, design, and performance of the plants and their potential environmental effects. This includes the identification of dominant risk contributors, determination of the vulnerabilities of plant and containment systems, and comparison of options for risk reduction. Three levels of PSA are recognized. Level-1 addresses the identification of plant failures leading to core damage and their frequencies of occurrence. Level-2 addresses the assessment of containment response leading together with level-1 results to the determination of containment release frequencies. A level-2 PSA analyses the challenges to the containment, the possible containment responses and their estimated probabilities, and an assessment of the consequent releases to the environment. Level-3 is the assessment of off-site consequences leading, together with the results of level-2 analysis, for estimation of public risks. A comprehensive level-2 PSA study of a 220 MWe Indian Pressurized Heavy Water Reactor (IPHWR) is performed to assess the challenges to the containment, the possible containment responses and their estimated probabilities, and consequent releases to the environment. The dominating sequences consist of small-break loss of coolant accident (SBLOCA) and station black out (SBO) followed by containment isolation failure. The results of this are used as an input for developing the severe accident management guidelines (SAMG) measures. All the SAMG measures incorporated in this study have been found as beneficial and resulted in reduced large early release frequency (LERF).

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.

Review of the Configuration Risk Management Methodologies

2021 ◽  
Author(s):  
Yuhang Zhang ◽  
Zhijian Zhang ◽  
He Wang ◽  
Lixuan Zhang ◽  
Dabin Sun
Keyword(s):  
Risk Management ◽  
Real Time ◽  
Nuclear Power ◽  
Safety Assessment ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Probabilistic Safety Assessment ◽  
Technical Specifications ◽  
Risk Monitor ◽  
Probabilistic Safety

Abstract To ensure nuclear safety and prevent or mitigate the consequences of accidents, many safety systems have been set up in nuclear power plants to limit the consequences of accidents. Even though technical specifications based on deterministic safety analysis are applied to avoid serious accidents, they are too poor to handle multi-device managements compared with configuration risk management which computes risks in nuclear power plants based on probabilistic safety assessment according to on-going configurations. In general, there are two methodologies employed in configuration risk management: living probabilistic safety assessment (LPSA) and risk monitor (RM). And average reliability databases during a time of interest are employed in living probabilistic safety assessment, which may be naturally applied to make long-term or regular management projects. While transient risk databases are involved in risk monitor to measure transient risks in nuclear power plants, which may be more appropriate to monitor the real-time risks in nuclear power plants and provide scientific real-time suggestions to operators compared with living probabilistic safety assessment. And this paper concentrates on the applications and developments of living probabilistic safety assessment and risk monitor which are the mainly foundation of the configuration risk management to manage nuclear power plants within safe threshold and avoid serious accidents.

Application of Probabilistic Safety Assessment in the Design of Instrumentation and Control Systems for Nuclear Power Plants

2017 ◽  
Author(s):  
Pengyi Peng ◽  
Weidong Liu ◽  
Zhichao Yang
Keyword(s):  
Risk Assessment ◽  
Optimal Design ◽  
System Design ◽  
Nuclear Power ◽  
Safety Assessment ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Probabilistic Safety Assessment ◽  
And Control ◽  
Probabilistic Safety

Instrumentation and control (I&C) systems in nuclear power plants (NPPs) have the ability to initiate the safety-related functions necessary to shut down the plants and maintain the plants in a safe shutdown condition. I&C systems of low reliability will bring risks to the safe operation of NPPs. A sufficient level of redundancy and diversity of I&C design to ensure the safety is a major focus when designing a new reactor. Usually multiple signal paths are included in an I&C system design. Meanwhile, besides the protection and safety monitoring system (PMS), other sub-systems of I&C such as the diverse actuation system (DAS) will be included as a diverse backup of PMS to perform the functions of reactor trip and engineered safety features actuation systems (ESFAS). However, the construction costs increase as the level of system redundancy and diversity grows. In fact, from the perspective of deterministic theory, an I&C system of only two chains can meet the single failure criterion. So how to obtain the balance of safety and economy is a challenging problem in I&C system designing. Probabilistic Safety Assessment (PSA) is the most commonly used quantitative risk assessment tool for decision-making in selecting the optimal design among alternative options. In this paper, PSA technique was used to identify whether the I&C system design offers adequate redundancy, diversity, and independence with sufficient defense-in-depth and safety margins in the design of a new reactor. Firstly, detailed risk assessment criteria for I&C design were studied and identified in accordance with nuclear regulations. Secondly, different designs were appropriately modeled, and the risk insights were provided, showing the balance of safety and economy of each design. Furthermore, potential design improvements were evaluated in terms of the current risk assessment criterion. In the end, the optimal design was determined, and uncertainty analyses were performed. The results showed that all four designs analyzed in this paper were met the safety goals in terms of PSA, but each design had a different impact on the balance of risk. As the support systems of the NPP we analyzed were relatively weak, loss of off-site power and loss of service water were two main risk contributors. The common cause failure of reactor trip breakers and the sensors of containment pressure were risk-significant. After identifying the major risk factors, the I&C design team can perform subsequent optimizations in the further design based on the PSA results and achieve an optimal balance between safety and economy.

Fuzzy methodology applied to Probabilistic Safety Assessment for digital system in nuclear power plants

2011 ◽  
Vol 241 (9) ◽  
pp. 3967-3976 ◽  
Author(s):  
Antonio César Ferreira Guimarães ◽  
Celso Marcelo Franklin Lapa ◽  
Maria de Lourdes Moreira
Keyword(s):  
Nuclear Power ◽  
Safety Assessment ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Digital System ◽  
Probabilistic Safety Assessment ◽  
Probabilistic Safety
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