Analysis Of Accident Scenarios Research Articles

Probabilistic safety analysis of the large primary circuit leakages accident scenarios in the VVER-reactor

Probabilistic safety analysis of the loss of coolant accidents in the VVER-type reactor plant has been performed taking into account the internal initiating events of the reactor primary circuit large leakages. Swedish program code RiskSpectrum PSA was used for probabilistic safety analysis. Logical probabilistic models of the accident scenarios of the large primary circuit leakages in the VVER-type reactor were developed taking into account different operation modes of the power plant unit. Critical paths and probabilities of the accident scenarios occurrence of the large leakages were identified. The critical path of development of the reactor primary circuit large leakages accident with large leakages of 140–346 mm diameters is the accident sequence with a leak in the pipeline to the reactor pressurizer vessel. It has been established that the greatest contribution to the failure of safety functions during this initiating event is made by the failures due to common causes of the supporting systems (cooling and ventilation systems), critical consumers cooling circuit, emergency injection system. The critical path of the accident with large leakages of 346–850 mm diameters is the accident sequence with the rupture of any of the four primary circuit loops. The greatest contribution to the failure of safety functions during this initiating event is made by the failures due to common causes of the emergency injection system elements. Based on the accident analysis, recommendations for increase of performance reliability of safety functions during the large leakages accidents under all operation states of the nuclear power plant unit were given. In order to increase reliability of safety systems, it is necessary to eliminate failures due to common causes of equipment, increase the reliability of operation of supporting systems, change the maintenance and checking equipment procedures.

Алгоритм оценки последствий отказа технологического трубопровода по методике API RP 581 3rd Edition (Уровень 1)

The article considers the issue of the development of an algorithm for the assessment of the consequences of failure (CoF) of the process pipeline of the gas condensate stabilization system of a hazardous production facility. The assessment of the consequences of failure is one of the main components of a risk-oriented approach to the inspection of technical devices. In accordance with the API RP 581 3rd Edition methodology, the assessment is used for equipment ranking and designed to determine the priority of inspections. Inspection, in turn, is a tool to ensure integrity, i.e., the condition of equipment that ensures its leak-tightness, which undoubtedly is a necessary condition of industrial safety. The algorithm and the detailed procedure of calculation of failure consequences consisting of 13 basic stages have been provided. As an example, the calculation of failure consequences has been conducted by the API RP 581 3rd Edition methodology (Level 1). The basic stages and the results of calculation have been compared to the calculation methodologies of technical device failure consequences effective in Russia. The results of the comparative analysis of methodologies indicate their similarity as to the application of common methods of the analysis of accident scenarios, the use of similar initial data, and the focus on the reduction of equipment failure risk. At the same time, significant differences in indices and criteria of acceptable risk level have been detected. The results of the calculation indicated the conservatism of the API 581 3rd Edition methodology (Level 1). The application of calculation of failure consequences by the API RP 581 3rd Edition methodology (Level 1) in the field of risk-oriented approach to the inspection of technical devices is possible upon its adaptation to the standards generally accepted in Russia.

Enhancing Test Driver Response Skills through Accident Scenario Analysis in Real-World Evaluation of Autonomous Vehicles

Enhancing Test Driver Response Skills through Accident Scenario Analysis in Real-World Evaluation of Autonomous Vehicles

Risk assessment and numerical analysis of short-term accident scenarios in a nuclear fuel storage vault

Analysis of various accident scenarios is vital for the safety assessment of nuclear fuel storage facilities. The accidents in the storage vault due to loss of cooling are generally considered highly uncertain since the accident progression is slow (in comparison to reactors) and allows time for remedial activities to the operator. In the present work, numerical simulations of different accident scenarios have been carried out for a short duration to understand the situation better. Thermal aspects of accident conditions such as failure of the suction blower, drying of cooling water at the chiller, and combined effect of both accidents were investigated. The airflow inside the ventilated enclosures due to the failure of the blower and the rise in inlet air temperature is analyzed numerically. The temperature distributions inside the vault and the rise in temperature of the sub-assemblies and magazines have been studied. The key mechanisms of heat transfer, which take part in nuclear fuel storage vault for post-accident conditions, were identified. The study will be helpful to classify various accident conditions based on their thermal implications and the model developed can be used to design passive cooling systems.

Analysis of nuclear accident scenarios and emergency planning zones for a proposed Advanced Power Reactor 1400 (APR1400)

Radiological scenario analysis considering potential accidents and the corresponding emergency planning arrangements are based on the estimations of radioactive releases following such accidents. This involves investigating the possible effects on the surrounding population and environment. The current paper hypothesized three accident scenarios in a pressurized water reactor (PWR) proposed to be located in Khor Duweihin on the Western Coast of the Arabian Gulf. HotSpot tool was used to estimate the total effective dose equivalent (TEDE) due to certain released radionuclides of different chemical groups. Initial emergency planning arrangements were defined based on the estimated doses triggered by the hypothetical scenarios considered: loss of coolant accident (LOCA), station blackout (SBO) and steam generator tube rupture (SGTR) in an Advanced Power Reactor 1400 (APR1400). This study established a baseline for an emergency plan that assures the mitigation of radiological consequences due to probable nuclear accidents, involving preparedness based on forecasting the atmospheric dispersion of radionuclides released during potential scenarios in different meteorological conditions.

Modeling the Diffusion of Radioactive Materials into the East Sea of Korea: Analysis of Hypothetical Nuclear Power Plant Accident Scenarios and Long-Term Marine Ecosystem Impacts

Min, B.I.; Suh, K.-S.; Park, K.; Kim, J.Y.; Choi, Y., and Kim, S., 2023. Modeling the diffusion of radioactive materials into the East Sea of Korea: Analysis of hypothetical nuclear power plant accident scenarios and long-term marine ecosystem impacts. Journal of Coastal Research, 39(2), 394–400. Charlotte (North Carolina), ISSN 0749-0208. The East Sea is surrounded by South Korea, North Korea, Japan, China, and Russia and is connected to the Northwest Pacific Ocean through three narrow straits. In the East Sea, there are 18 nuclear power plants installed along the coasts of South Korea alone. This study evaluated the long-term diffusion of radioactive materials in the East Sea using a compartment model and described the effect on a marine food chain model. A hypothetical scenario in which soil near the power plant is contaminated and flows into rivers and seas due to rainfall was numerically tested. It took about 2 minutes to calculate the intake dose for 10 years, and there was no significant difference compared to the detailed model.

Initial accident scenario analysis in support of a preliminary DEMO tritium plant design

An initial safety analysis of a preliminary DEMO tritium fuel cycle has been undertaken using functional failure mode and effects analysis (FFMEA) to create accident scenarios for evaluation. A total of ten scenarios were developed and analysed based upon the current technology planned for the tritium fuel cycle. The findings indicate that the potential radioactive hazards from accident scenarios would result in increased dose rates to workers but that these rates can be kept within manageable levels through proper ventilation, backup systems, and engineered safety. The individual hazards found within the tritium fuel cycle are echoed in other processing industries, and knowledge transfer from well-established industries will enhance the safety procedures. The methodology for identifying and evaluating accident scenarios put forth in this paper can be used as the design of the fuel cycle progresses to maturity.

Integration of Fire Safety Barriers in the Probabilistic Analysis of Accident Scenarios Triggered by Lightning Strike on Atmospheric Storage Tanks

Integration of Fire Safety Barriers in the Probabilistic Analysis of Accident Scenarios Triggered by Lightning Strike on Atmospheric Storage Tanks

Experimental investigation of side-discharge sparger on pressure oscillation in steam jet condensation

Experiments were conducted to investigate the pressure oscillation of steam jet condensation through a side-discharge sparger in stagnant water. Simultaneous analysis based on the synchronous measurement in the time domain was conducted between pressure oscillation and steam interfacial behaviors, and quantitative discussion about the intensity was taken according to the power spectrum of pressure oscillation. First, a regime map suitable for a sparger of 16 mm was presented and the bubbling, chugging, and jetting regimes were observed in this experiment. Compared with other regime maps, the bubbling regime is more narrow in the range of the steam mass flux when it is at low temperature, while is wider at high temperature. Second, it was found that different frequencies dominate the pressure oscillation under different conditions named the collapse frequency, the condensation frequency, and the generation frequency. The collapse frequency created by the collapse of detached bubbles prevails in the region with the temperature higher than 75 °C, while the condensation frequency induced by the condensation of bubbles controls the pressure oscillation in regions with the temperature lower than 60 °C. The generation frequency caused by the generation of bubbles mainly appears in the bubbling regime and is the secondary influence of pressure oscillation. This work provides a better understanding of steam jet condensation and could be helpful for the analysis of accident scenarios of pressure suppression systems.

Using Machine Learning to Predict the Fuel Peak Cladding Temperature for a Large Break Loss of Coolant Accident

In this paper the use of machine learning (ML) is explored as an efficient tool for uncertainty quantification. A machine learning algorithm is developed to predict the peak cladding temperature (PCT) under the conditions of a large break loss of coolant accident given the various underlying uncertainties. The best estimate approach is used to simulate the thermal-hydraulic system of APR1400 large break loss of coolant accident (LBLOCA) scenario using the multidimensional reactor safety analysis code (MARS-KS) lumped parameter system code developed by Korea Atomic Energy Research Institute (KAERI). To generate the database necessary to train the ML model, a set of uncertainty parameters derived from the phenomena identification and ranking table (PIRT) is propagated through the thermal hydraulic model using the Dakota-MARS uncertainty quantification framework. The developed ML model uses the database created by the uncertainty quantification framework along with Keras library and Talos optimization to construct the artificial neural network (ANN). After learning and validation, the ML model can predict the peak cladding temperature (PCT) reasonably well with a mean squared error (MSE) of ∼0.002 and R2 of ∼0.9 with 9 to 11 key uncertain parameters. As a bounding accident scenario analysis of the LBLOCA case paves the way to using machine learning as a decision making tool for design extension conditions as well as severe accidents.

Evidence based risk analysis of fire and explosion accident scenarios in FPSOs

The paper proposes a methodology for risk assessment and probabilistic modelling of fire and explosion accidents in Floating production storage and offloading (FPSO) units. The overall objective of the paper is to propose a Bayesian Network probabilistic framework towards quantification of fire and explosion events in FPSOs derived from a systematic analysis of incidental and accidental scenarios specific to FPSOs. A data set of around 800 incidents in FPSOs from various open-source agencies is prepared and analysed. The key features of the incidents are discussed and the relationships amongst the significant variables influencing the types of incidents are assessed. The circumstances of potential incidents related to fire and explosions are discussed. A detailed risk analysis is conducted using the risk matrix approach to screen and rank the major accidents occurring in FPSOs. Then, a Bayesian Network model of high-risk fire and explosion scenarios is developed based on evidences obtained from accident reports and expert opinions. The model uses a framework based on immediate causes, basic causes and causal factors to demonstrate various accidental scenarios specific to FPSOs. A sensitivity analysis is conducted to identify the most important causal factors and the aspects that need more research work for decision-making. The contribution of the present study is threefold: a methodology for comprehensive risk assessment in FPSOs is proposed; FPSO specific incidents and accidents are characterized; a probabilistic model for fire and explosion scenarios is developed from a causal framework. The results of the paper provide FPSO developers and operators with information to prevent and mitigate fire and explosion accidents.

A numerical study of thermal behavior of CASTOR RBMK-1500 cask under fire conditions

Casks are widely used for interim storage of spent nuclear fuel after its pre-storage in water pools. Interim storage of spent nuclear fuel is a very important part in the whole cycle of nuclear energy generation, so the casks must be designed according to relevant safety standards. Like criticality and doses, thermal safety is an important condition for spent nuclear fuel storage in a dry spent nuclear fuel storage facility and should be analyzed thoroughly. During the entire period of interim storage of spent nuclear fuel, normal operation and emergency situations should be investigated. Analysis of various accident scenarios is one of the means to prevent damage of storage casks and spent nuclear fuel. There are many publications on thermal cask behavior during normal operation conditions, yet publications on cask behavior during accidents are rather limited. There are a few publications presenting fire impact analysis of thermal behavior of casks during transportation. Therefore, this paper presents a numerical study that has been performed to evaluate thermal behavior of a cask under fire condition loaded with spent nuclear fuel stored in an open type dry storage facility pre-stored in a water pool for five years. Thermal performance of a 2D vertical CASTOR RBMK-1500 cask under such conditions (steady-state, fire, post-fire) has been numerically studied by using the ANSYS Fluent code. Also, a local sensitivity analysis of parameters that mostly influence the cask’s temperature was performed.

Computational Modelling and Prediction of Consequences in Case of Accidental Releases of Hazardous Substances in an Industrial Plant

Storing relatively large amounts of hazardous materials under certain conditions can lead to high-risk situations. In industrial units, the assessment of the amplitude and severity of the consequences of the identified major accidents is done in order to provide data on site intervention and emergency planning. This study aims to assess the consequences of untimely releases of hazardous explosive / toxic substances in an industrial unit by graphical modelling and analysis of such accident scenarios using specialized software tools. The main activity of the industrial unit under study consists in the manufacture, processing and marketing of essential oils and their derived products.

Identification and Analysis of Accident Scenarios in the Hospital Central Oxygen Unit by Fault Tree Analysis Method and Evaluation of the Adequacy of Control Devices Using Layer of Protection Analysis

Identification and Analysis of Accident Scenarios in the Hospital Central Oxygen Unit by Fault Tree Analysis Method and Evaluation of the Adequacy of Control Devices Using Layer of Protection Analysis

Network theory-based accident scenario analysis for hazardous material transport: A case study of liquefied petroleum gas transport in Japan

ABSTRACT To analyze an accident scenario involving the transport of hazardous material (HAZMAT), a complex accident process must be completely described; however, existing analytical approaches, which are influenced by the arbitrariness of a given analyst, may not cover the entire process. Thus, the aim of this study is to develop a new approach for analyzing accident scenarios associated with HAZMAT transport, using network theory as a key to illustrate the complex accident process. In the developed approach, accident scenarios are sampled from the accident processes by fusing the HAZMAT transport accident network and transport environmental factors, based on accident data. The proposed approach was applied to a case of Liquefied petroleum gas (LPG) transport by road in Japan. The case study identified 68,874 scenarios and classified the identified scenarios into three types of risk categories: 80 high-risk, 9,112 medium-risk, and 59,682 low-risk scenarios. It was observed that the scenarios identified could successfully help understand the complex accident processes in HAZMAT transport and incorporate the safety measures through the accident network. The proposed approach for accident scenario analysis can accelerate the risk assessment of HAZMAT transport and help advance risk assessment to risk management.

An innovative quantitative analysis methodology for Natech events triggered by earthquakes in chemical tank farms

Natech events triggered by earthquakes are one of the major threats in chemical clusters. Earthquake can not only cause serious damage to equipment, but also hinder the rescue operations and exacerbate the evolution and escalation of accidents. In order to analyze the complicated domino accident scenarios under earthquake in chemical tank farms, an innovative quantitative analysis method is proposed. The algorithm based on Monte Carlo simulation for domino probabilities considers the multiple escalation vectors of the same accident unit and the synergistic effect of multiple escalation vectors from different units. Domino probabilities at different levels can be analyzed for specific primary scenario and overall scenarios. Two different rescue operation states considering and not considering the impact of earthquake are analyzed in case study. The results show that earthquake greatly increases the risk of chemical tank farm and rescue operations with longer time lead to higher domino probabilities due to higher escalation probabilities; the domino accident evolves faster and has higher probabilities in the primary scenario with multiple accident sources; the domino probabilities above third level are small for overall scenarios, especially in the case of high earthquake intensity. The methodology can also be applied to the analysis of complex specific accident scenarios and provide support for the setting of safety barriers and emergency resources.

Bayesian perspective in BEPU licensing analysis

The main objective of this paper is giving insights about the Bayesian formulation of Best-Estimate-Plus-Uncertainty (BEPU) methodologies of Nuclear Safety. It is written from a regulatory standpoint, focusing on the assessment and licensing process of this type of methodologies. The current use of Bayesian methods in Uncertainty Quantification (UQ) is summarized, distinguishing Forward and Inverse UQ. In Forward UQ, the most popular methods are frequentist and nonparametric. They are based on a minimum of assumptions, and this fact makes them simple to use and may expedite their assessment and licensing process, compared to other methods. Bayesian formulations, on the other hand, need to adequately justify the choice of prior distributions, to make sure that uncertainties are not estimated in an anticonservative fashion.Concerning Forward UQ, methods based on calculation of probabilities of exceeding regulatory limits (P-methods) are an alternative to standard methods based on quantile estimation (Q-methods). A frequentist P-method, the Clopper-Pearson interval, is basically equivalent to the noted Wilks’ method, and so it is extensively used in the BEPU realm. Bayesian framework has been typically overlooked in the realm of P-methods for licensing purposes. The possibility of using such formulation to implement prior information about previous BEPU analysis of similar plant designs, operational conditions and accident scenarios should be explored. Bayesian methodologies of this type are used in Reliability, and they combine specific data with generic data (in the form of priors) of component or system failures.In inverse UQ, the situation is opposite to forward UQ: Bayesian methodologies are preferred to frequentist ones. One of the main reasons may be that Bayesian formulation produce regularized (well-posed) solutions to inverse problems.

Development of a 3D thermohydraulic-neutronic coupling model for accident analysis in research miniature neutron source reactor (MNSR)

Abstract To accurately analyze the accidents in nuclear reactors, a thermohydraulic-neutronic coupling calculation is required to solve fluid dynamics and nuclear reactor kinetics equations in fine cells simultaneously and evaluate the local effects of neutronic and thermohydraulic parameters on each other. In the present study, a 3D thermohydraulic-neutronic coupling model is developed, validated and then applied for Isfahan MNSR (Miniature Neutron Source reactor) safety analysis. The proposed model is developed using FLUENT software and user defined functions (UDF) are applied to simulate the neutronic behavior of MNSR. The validation of the proposed model is first evaluated using 1mk reactivity insertion experiment into Isfahan MNSR core. Then, the developed coupling code is applied for a design basis accident (DBA) scenario analysis with the insertion of maximum allowed cold core reactivity of 4 mk. The results show that the proposed model is able to predict the behavior of the reactor core under normal and accident conditions with a good accuracy.

A model-based system engineering approach to manage railway safety-related decisions

The safety assessment of Safety Critical Systems (SCSs) is a challenging task since it involves different actors and a combination of several knowledge domains. This increases the complexity of the integration of safety requirements into the design model. Consequently, there is a need for a shared model with an unambiguous terminology aiming to avoid misunderstandings between both safety and design teams. In this paper, we propose a model-based system engineering approach in order to support the goal-oriented safety reasoning and to provide a common model between both safety and requirement engineering driven by goals. Furthermore, the present study considers the safety rules development process based on the Organization-based Access Control (Or-BAC) model, which is normally used to improve the security of the information systems. Then, the common vocabulary proposed for the inter- pretation of the considered notions of domains is defined. Moreover, safety requirements are expressed with a high level of abstraction according to the required railway knowledge and the requirement trace- ability process is considered through an up-bottom reasoning using the Unified Modeling Language (UML) diagrams. The proposed approach aims to provide a methodology able to identify safety conditions in order to anticipate risks and to make better safety-related decisions. Finally, the proposed methodology is evaluated through a real accident scenario analysis in order to validate its adaptability to represent real critical situations.

ATWS severe accident analysis in the loss of flow scenario using the MELCOR code in Bushehr nuclear Power Plant

Abstract The analysis of accident scenarios in a nuclear power plant and consequently a review of the proper functioning of safety systems is very importance. In this paper, an analysis of a anticipated transient without scram has been done in the Loss of flow scenario with modeling the VVER-1000 reactor of Bushehr by MELCOR1.8.6 code. The chronological sequence of the different steps and the history of the parameters under this accident calculated with the code are evaluated. Parameters such as temperature and pressure changes in the primary and secondary circuit, temperature changes of fuel and fuel clad are calculated as well as a comparison with the melting temperature. Also, the rate of hydrogen production and pouring molten material into the reactor cavity is calculated. This information is very useful for managing the ATWS accident and controlling the reactor. Also, this results to assess Bushehr nuclear power plant. The results show that thermodynamic parameters of pressure and temperature passes the limit without any accident management.