The Assessment of Containment Functional Failure Frequency in the Revised Level 2 PRA Standard in Japan

2016 ◽  
Author(s):  
Ryoichi Hamazaki ◽  
Kazunori Hashimoto ◽  
Takayoshi Kusunoki ◽  
Chikahiro Satou
Keyword(s):  
Steam Explosion ◽  
Human Error ◽  
Severe Accident ◽  
Event Tree ◽  
Complementary Information ◽  
Functional Failure ◽  
Failure Frequency ◽  
Operation Status ◽  
Level 2 ◽  
Containment Integrity

In this paper, we introduce the overview of the requirements and the complementary information on the evaluation of containment functional failure frequency (CFF) in the revised version of “A Standard for Procedures of Probabilistic Risk Assessment of Nuclear Power Plants during Power Operation (Level 2 PRA) “[1] in Japan, which was developed and revised at the Level 2 PRA Subcommittee under the Atomic Energy Society of Japan (AESJ). Although the Level 2 PRA standard includes the evaluation of CFF and radiological source terms, we explain only the evaluation of CFF in this paper. In the evaluation of CFF, the physical response analysis and the probabilistic analysis are included as follows. The accident progression analysis is performed for each of the plant damage states, considering the operation status of mitigation systems, thermal-hydraulic behavior and core damage progression, and occurrences of some key events such as reactor pressure vessel failure. The containment event tree (CET) is developed classifying the accident progress in tree diagram. In the CET, some headings are arranged sequentially considering the accident progression. The headings correspond to the phenomena occurrence and the systems operation status, and a branch probability is assigned at each branch of heading. The branch probabilities of the phenomena are evaluated by either the Risk Oriented Accident Analysis Methodology (ROAAM) or the Decomposition Event Tree (DET) analysis considering the containment threats. The branch probabilities on the phenomena are set as the probability distributions, because the phenomena and the analysis have uncertainties. The branch probabilities on the systems operation are evaluated using the fault tree analysis and human error analysis. The containment functional failure modes are assigned at the end state of the CET considering the type of load against containment integrity. For the evaluation of the non-energetic load, the integral codes such as MELCOR [2], THALES-2 [3], and MAAP4 [4] etc. are used. On the other hand, various mechanistic codes are used for the evaluation of energetic phenomena such as steam explosion. The containment functional failure is judged by comparing the ultimate strength or the fragility of containment structure and the generated loads. After all, the CFF can be obtained by summing the frequency of containment functional failure mode. In the Level 2 PRA standard in Japan, the requirements in each evaluation process above are described. In addition, the technical background and the examples as the complementary information on each requirement are described in the Annex of the standard to help the application of the standard. In this revision, the body is revised to clarify the requirements on the quantification of the CET. The Annex is revised to incorporate the up-to-date information on severe accident research and severe accident management (SAM) measures. The updated information includes the melt stratification (OECD/MASCA project [5]), the steam explosion (SERENA project [6] and PULiMS/SES experiments [7]), the ex-vessel debris coolability (OECD/MCCI project [8]), debris jet breakup, the melt spreading, the coolability of the particulate bed, and the containment vessel (CV) fragility evaluation. Some future challenges are extracted from the lessons learned from the Fukushima Daiichi accident, such as development of the Level 2 PRA for the external hazard as earthquake and tsunami, quantification of impact on the containment integrity of hydrogen detonation in the adjacent buildings, and human error evaluation in the external hazard.

Comparative Calculations of TROI TS-2 and TS-3 Steam Explosion Experiments With TEXAS-V

2017 ◽  
Author(s):  
Taehoon Kim ◽  
Sukyoung Pak ◽  
Yongjin Cho
Keyword(s):  
Void Fraction ◽  
Steam Explosion ◽  
Peak Pressure ◽  
Severe Accident ◽  
Experiment Data ◽  
Trigger Time ◽  
Vessel Reactor ◽  
The Moment ◽  
Containment Integrity ◽  
Good Agreement

During a severe accident, contact of the molten corium with the coolant water may cause an energetic steam explosion which is a rapid increase of explosive vaporization by transfer to the water of a significant part of the energy in the corium melt. This steam explosion has been considered as an adverse effect when the water is used to cool the molten corium and could threaten reactor vessel, reactor cavity, containment integrity. In this study, TROI TS-2 and TS-3 experiments as part of the OECD/SERENA-2 project were analyzed with TEXAS-V. Input parameters were based on actual TROI experiment data. In mixing simulations, calculated results were compared to melt front behavior, void fraction in trigger time and other parameters in experiment results. In explosion simulations, corresponding to TROI experiments an external triggering was employed at the moment that melt front reached heights of 0.4 m. Calculated results of peak pressure and impulse at the bottom were compared with TROI experiment results. Melt front behaviors of the melt was different from the experimental results in both TS-2 and TS-3. Void fraction in triggering time in TS-2 was in good agreement with the experiment results and in TS-3 was slightly overestimated. The peak pressure and impulse at bottom were successfully predicted by TEXAS-V. These calculations will allow establishing whether the limitations and differences observed in the simulations of the experiments are important for the reactor case.

Numerical Simulation of Corium Jet Breakup During Fuel-Coolant Interaction Based on the ALISA Test Performed at KROTOS Test Facility

2018 ◽  
Author(s):  
Pei Shen ◽  
Wenzhong Zhou
Keyword(s):  
Numerical Simulation ◽  
Steam Explosion ◽  
Field Method ◽  
Severe Accident ◽  
Phase Field Method ◽  
Test Facility ◽  
Jet Breakup ◽  
Jet Behavior ◽  
Jet Fragmentation ◽  
Explosion Test

Steam explosion is one of the consequences of fuel-coolant interactions in a severe accident. Melt jet fragmentation, which is the key phenomenon during steam explosion, has not been clarified sufficiently which prevents the precise prediction of steam explosion. The focus of this paper is on the numerical simulation of the melt jet behavior falling into a coolant pool in order to get a qualitative and quantitative understanding of initial premixing stage of fuel-coolant interaction. The objective of our first phase is the simulation of the fragmentation process and the estimation of the jet breakup length. A commercial CFD code COMSOL is used for the 2D numerical analysis employing the phase field method. The simulation condition is similar to our steam explosion test supported by the ALISA (Access to Large Infrastructure for Severe Accidents) project between European Union and China, and carried out in the KROTOS test facility at CEA, France. The simulation result is in relatively good agreement with the experimental data. Then the effect of the initial jet velocity, the jet diameter and the instability theory are presented. The preliminary data of melt jet fragmentation is helpful to understand the premixing stage of the fuel-coolant interaction.

Identification of Human Errors During Early Design Stage Functional Failure Analysis

2018 ◽  
Author(s):  
Lukman Irshad ◽  
Salman Ahmed ◽  
Onan Demirel ◽  
Irem Y. Tumer
Keyword(s):  
Failure Analysis ◽  
Human Error ◽  
System Level ◽  
Design Stage ◽  
Human Factors Engineering ◽  
Human Errors ◽  
Functional Failure ◽  
Early Design ◽  
Early Design Stage ◽  
Early Design Stages

Detection of potential failures and human error and their propagation over time at an early design stage will help prevent system failures and adverse accidents. Hence, there is a need for a failure analysis technique that will assess potential functional/component failures, human errors, and how they propagate to affect the system overall. Prior work has introduced FFIP (Functional Failure Identification and Propagation), which considers both human error and mechanical failures and their propagation at a system level at early design stages. However, it fails to consider the specific human actions (expected or unexpected) that contributed towards the human error. In this paper, we propose a method to expand FFIP to include human action/error propagation during failure analysis so a designer can address the human errors using human factors engineering principals at early design stages. To explore the capabilities of the proposed method, it is applied to a hold-up tank example and the results are coupled with Digital Human Modeling to demonstrate how designers can use these tools to make better design decisions before any design commitments are made.

Computational Functional Failure Analysis to Identify Human Errors During Early Design Stages

2019 ◽  
Vol 19 (3) ◽  
Author(s):  
Lukman Irshad ◽  
Salman Ahmed ◽  
H. Onan Demirel ◽  
Irem Y. Tumer
Keyword(s):  
Failure Analysis ◽  
Human Error ◽  
Human Action ◽  
System Level ◽  
Design Stage ◽  
Human Factors Engineering ◽  
Human Errors ◽  
Functional Failure ◽  
Early Design ◽  
Early Design Stages

Detection of potential failures and human error and their propagation over time at an early design stage will help prevent system failures and adverse accidents. Hence, there is a need for a failure analysis technique that will assess potential functional/component failures, human errors, and how they propagate to affect the system overall. Prior work has introduced functional failure identification and propagation (FFIP), which considers both human error and mechanical failures and their propagation at a system level at early design stages. However, it fails to consider the specific human actions (expected or unexpected) that contributed toward the human error. In this paper, we propose a method to expand FFIP to include human action/error propagation during failure analysis so a designer can address the human errors using human factors engineering principals at early design stages. The capabilities of the proposed method is presented via a hold-up tank example, and the results are coupled with digital human modeling to demonstrate how designers can use these tools to make better design decisions before any design commitments are made.

Level 2 PSA Overview of HPR1000 Nuclear Power Plant

2020 ◽  
Author(s):  
Wang Ziguan ◽  
Lu Fang ◽  
Yang Benlin ◽  
Chen Shi ◽  
Hu Lingsheng
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Heat Removal ◽  
Accident Prevention ◽  
Severe Accident ◽  
Mitigation Measures ◽  
Injection System ◽  
Risk Level ◽  
Level 2

Abstract Risk-informed design approaches are comprehensively implemented in the design and verification process of HPR1000 nuclear power plant. Particularly, Level 2 PSA is applied in the optimization of severe accident prevention and mitigation measures to avoid the extravagant redundancy of system configurations. HPR1000 preliminary level 2 PSA practices consider internal events of the reactor in the context of at-power condition. Severe accidents mitigation and prevention system and its impact on the overall large release frequency (LRF) level are evaluated. The results showed that severe accident prevention and mitigation systems, such as fast depressurization system, the cavity injection system and the passive containment heat removal system perform well in reducing LRF and overall risk level of HPR1000 NPP. Bypass events, reactor rapture events, and the containment bottom melt-through induced by MCCI are among the dominant factors of the LRF. The level 2 PSA analysis results indicate that HPR1000 design is reliable with no major weaknesses.

Study on Methodology and Application of Seismic-Induced Flood Level 2 PSA for PWR in China

2020 ◽  
Author(s):  
Liu Yu ◽  
Li Wenjing ◽  
Yu Yun
Keyword(s):  
Severe Accident ◽  
Key Factors ◽  
Fukushima Accident ◽  
Core Damage ◽  
Design Basis ◽  
Flood Level ◽  
Crucial Problem ◽  
External Events ◽  
Flood Characteristics ◽  
Level 2

Abstract Level 2 (L2) PSA is focused on the severe accident phenomenon, progression and source terms release to generally evaluate the containment response after core damage takes place. Fukushima accident was caused by seismic and tsunami which are beyond design basis. It indicates that evaluating the risk for extremely external hazards is vitally important. Therefore, how to perform the study on L2 PSA for external events (especially seismic and flood) has become a crucial problem needed to be considered deeply for both regulators and operators. In this paper, the methodology of flood and seismic-induced flood L2 PSA was developed and applied for a Gen III NPP in China. The key factors include: (1) Focusing on crucial elements of L2 PSA in view of seismic and flood characteristics, including PSA interfaces, design features, severe accident phenomenon and progression, containment performance analysis, etc. (2) Building integrated internal flood and seismic L2 PSA models. (3) Developing an analytical method to evaluate seismic-induced flood L2 PSA.

Application of Level 2 PSA in the Design of Cavity Injection System for Nuclear Power Plant

2018 ◽  
Author(s):  
Wentao Zhu ◽  
Wenjing Li
Keyword(s):  
Decision Making ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Assessment Tool ◽  
Quantitative Risk Assessment ◽  
Severe Accident ◽  
Injection System ◽  
Retention Strategy ◽  
Level 2

After Fukushima nuclear power plant accident, severe accident is getting more and more concerns all over the world. In order to mitigate severe accident and improve the safety of nuclear power plant, two different strategies are applied in different plants. One is in-vessel melt retention strategy, and the other is ex-vessel melt retention strategy. Tianwan nuclear power plant is an improved Gen II nuclear power plant and in-vessel melt retention strategy is adopted in the plant. In order to achieve this strategy, cavity injection system is designed for the plant. Probabilistic Safety Analysis is the most commonly used quantitative risk assessment tool for decision-making in selecting the optimal design among alternative options. For this plant, in order to optimize the design of cavity injection system, improve the safety level of nuclear power plant, and meanwhile, improve the engineering implementation and economization, Level 2 PSA was used for this decision-making process. In this paper, the Level 2 PSA for this plant and the application for the design of cavity injection system are introduced.

Development of Accidental Scenarios Involving Human Errors for Risk Assessment in Restricted Waters

2020 ◽  
Author(s):  
Danilo Taverna Martins Pereira de Abreu ◽  
Marcos Coelho Maturana ◽  
Marcelo Ramos Martins
Keyword(s):  
Human Error ◽  
Human Performance ◽  
Typical Feature ◽  
Performance Model ◽  
Traffic Density ◽  
Technical Failure ◽  
Event Tree ◽  
Analysis Model ◽  
Event Tree Analysis ◽  
Tree Analysis

Abstract The navigation in restricted waters imposes several challenges when compared to open sea navigation. Smaller dimensions, higher traffic density and the dynamics of obstacles such as sandbanks are examples of contributors to the difficulty. Due to these aspects, local experienced maritime pilots go onboard in order to support the ship’s crew with their skills and specific regional knowledge. Despite these efforts, several accidents still occur around the world. In order to contribute to a better understanding of the events composing accidental sequences, this paper presents a hybrid modelling specific for restricted waters. The main techniques used are the fault tree analysis and event tree analysis. The former provides a framework to investigate the causes, while the latter allows modelling the sequence of actions necessary to avoid an accident. The models are quantified using statistical data available in the literature and a prospective human performance model developed by the Technique for Early Consideration of Human Reliability (TECHR). The results include combined estimates of human error probabilities and technical failure probabilities, which can be used to inform the causation factor for a waterway risk analysis model. In other words, given that the ship encounters a potential accidental scenario while navigating, the proposed models allow computing the failure probability that of the evasive actions sequence. The novelty of this work resides on the possibility of explicitly considering dynamicity and recovery actions when computing the causation factor, what is not a typical feature of similar works. The results obtained were compared with several results available in the literature and have been shown to be compatible.

scholarly journals Statistical Analysis and Prediction of Fatal Accidents in the Metallurgical Industry in China

2020 ◽  
Vol 17 (11) ◽  
pp. 3790 ◽  
Author(s):  
Qingwei Xu ◽  
Kaili Xu
Keyword(s):  
Metallurgical Industry ◽  
Grey System Theory ◽  
Severe Accident ◽  
Event Tree ◽  
Grey System ◽  
Event Tree Analysis ◽  
Safety Measures ◽  
Fatal Accidents ◽  
Tree Analysis ◽  
Bow Tie

The metallurgical industry is a significant component of the national economy. The main purpose of this study was to establish a composite risk analysis method for fatal accidents in the metallurgical industry. We collected 152 fatal accidents in the Chinese metallurgical industry from 2001 to 2018, including 141 major accidents, 10 severe accidents, and 1 extraordinarily severe accident, together resulting in 731 deaths. Different from traffic or chemical industry accidents, most of the accidents in the metallurgical industry are poisoning and asphyxiation accidents, which account for 40% of the total number of fatal accidents. As the original statistical data of fatal accidents in the metallurgical industry have irregular fluctuations, the traditional prediction methods, such as linear or quadratic regression models, cannot be used to predict their future characteristics. To overcome this issue, the grey interval predicting method and the GM(1,1) model of grey system theory are introduced to predict the future characteristics of fatal accidents in the metallurgical industry. Different from a fault tree analysis or event tree analysis, the bow tie model integrates the basic causes, possible consequences, and corresponding safety measures of an accident in a transparent diagram. In this study, the bow tie model was used to identify the causes and consequences of fatal accidents in the metallurgical industry; then, corresponding safety measures were adopted to reduce the risk.

Sign in / Sign up

Export Citation Format

Share Document