Potential Accident Scenarios Research Articles

Arctic shipping accident scenario analysis using Bayesian Network approach

This paper presents a methodology for the analysis of Arctic shipping accident scenarios using Bayesian Networks (BN). The proposed methodology is applied to a scenario involving a collision between a vessel and an iceberg. The study aims to identify the most significant causative factors to the potential accident scenarios. It is achieved by undertaking a sensitivity analysis study. The results inform the development of measures to avoid and control accidents during Arctic shipping.

A software tool for integrated risk assessment of spent fuel transportation and storage

Abstract When temporary spent fuel storage pools at nuclear power plants reach their capacity limit, the spent fuel must be moved to an alternative storage facility. However, radioactive materials must be handled and stored carefully to avoid severe consequences to the environment. In this study, the risks of three potential accident scenarios (i.e., maritime transportation, an aircraft crashing into an interim storage facility, and on-site transportation) associated with the spent fuel transportation process were analyzed using a probabilistic approach. For each scenario, the probabilities and the consequences were calculated separately to assess the risks: the probabilities were calculated using existing data and statistical models, and the consequences were calculated using computation models. Risk assessment software was developed to conveniently integrate the three scenarios. The risks were analyzed using the developed software according to the shipment route, building characteristics, and spent fuel handling environment. As a result of the risk analysis with varying accident conditions, transportation and storage strategies with relatively low risk were developed for regulators and licensees. The focus of this study was the risk assessment methodology; however, the applied model and input data have some uncertainties. Further research to reduce these uncertainties will improve the accuracy of this model.

Comparison of UDM and CFD simulations of a time varying release of LPG in geometrical complex environment

The paper discusses the release and air dispersion modelling for the specific potential accident scenario case of a vertical impinging jet of propane (below the sun shade/rain roof) out of an over-filled car tanker. The main purpose was to assess the related uncertainties in impact distances downwind to the Lower Flammability Limit (LFL) and half the LFL (LFL/2) propane concentrations in the ambient air, due to the proximity of the site border (issue of the control over the ignition sources). The conventional Unified Dispersion Modelling (UDM) results were re-modelled using a dynamic process simulation (to simulate the pressure safety release valve) and dispersion modelling using a Computational Fluid Dynamic (CFD) model simulation. The CFD model enabled explicit consideration of the 3D objects and impinging jet. The comparison of the impact distances down to LFL and LFL/2 concentrations among UDM and CFD models revealed that the CFD model suggests the distances are about 2-3 times shorter, but the fire hazard (propane-air mixture) is present for approximately twice the time after cessation of the propane release. This means that conventional UDM derived results using the integrated models are to some extent conservative, while on the other hand, the duration of the fire hazard is underestimated. The results are important for risk analysts in terms of the consideration of the use of the UDM models out of the validated contexts (e.g., vertical impinging, obstacles), as well as for site managers in considering whether the ignition prevention measures (separation distances) are sufficient.

Epistemic-based investigation of the probability of hazard scenarios using Bayesian network for the lifting operation of floating objects

Owing to the increase in unprecedented accidents with new root causes in almost all operational areas, the importance of risk management has dramatically risen. Risk assessment, one of the most significant aspects of risk management, has a substantial impact on the system-safety level of organizations, industries, and operations. If the causes of all kinds of failure and the interactions between them are considered, effective risk assessment can be highly accurate. A combination of traditional risk assessment approaches and modern scientific probability methods can help in realizing better quantitative risk assessment methods. Most researchers face the problem of minimal field data with respect to the probability and frequency of each failure. Because of this limitation in the availability of epistemic knowledge, it is important to conduct epistemic estimations by applying the Bayesian theory for identifying plausible outcomes. In this paper, we propose an algorithm and demonstrate its application in a case study for a light-weight lifting operation in the Persian Gulf of Iran. First, we identify potential accident scenarios and present them in an event tree format. Next, excluding human error, we use the event tree to roughly estimate the prior probability of other hazard-promoting factors using a minimal amount of field data. We then use the Success Likelihood Index Method (SLIM) to calculate the probability of human error. On the basis of the proposed event tree, we use the Bayesian network of the provided scenarios to compensate for the lack of data. Finally, we determine the resulting probability of each event based on its evidence in the epistemic estimation format by building on two Bayesian network types: the probability of hazard promotion factors and the Bayesian theory. The study results indicate that despite the lack of available information on the operation of floating objects, a satisfactory result can be achieved using epistemic data.

The qualitative risk assessment of an electrolytic hydrogen generation system

A risk assessment for an electrolytic hydrogen generation system was carried out. The potential accident scenarios for the system were evaluated with a hazard and operability study (HAZOP) and failure mode effect analysis (FMEA). Brainstorming sessions were conducted to evaluate the possibility of each potential accident scenario. In the severity analysis for each potential accident scenario, the jet flame length was estimated based on an empirical formula using reference data. The blast pressure was mainly estimated by using the results of the reference. The risks of all potential hazards with and without the implementation of various safety measures were analyzed using risk matrices. It is clear that with the safety measures in place, the risk levels of all system hazards are acceptable.

Quantitative risk analysis on leakage failure of submarine oil and gas pipelines using Bayesian network

Submarine pipeline is the major transportation way of subsea oil and gas production. Due to the internal and external factor, the failure probability of submarine pipeline is increasing, which could lead to the spill accidents of oil and gas. Efficient risk analysis is vital for preventing and mitigating such potential accident. This paper presents a risk-based accident model to conduct quantitative risk analysis (QRA) for leakage failure of submarine pipeline. Firstly, we employ bow-tie method to model the causal relationship between pipeline leakage and potential accident scenarios. Subsequently, in order to overcome the difficulties of bow-tie in modeling uncertainties and conditional dependency, a Bayesian network model for pipeline leakage is developed through mapping from the former bow-tie. Meanwhile, an object-oriented Bayesian network that has a smaller and more clarified structure is also constructed by modularizing the primary Bayesian network. Eventually, the probability updating is implemented in risk analysis using Bayesian network when a new evidence or observation occurs, and an experience learning from accident precursor data is also conducted through Bayesian approach. The proposed accident model based on Bayesian network can provide a more case-specific and realistic analysis consequence compared to bow-tie method, since it could consider the common cause failures and conditional dependency in accident evolution process of pipeline leakage.

Comparative risk assessment of exploitation of old and new thermal power plant's ash disposal sites in Kostolac, according to hydrological scenario

In this paper a comparative risk assessment of the exploitation of old and new ash disposal sites in Kostolac is given. Risk assessment is carried out according to the FMEA (Failure Modes and Effects Analysis) method in combination with a risk matrix, which includes a detailed elaboration of potential accident scenario at disposal sites and analysis of consequences that accident can cause. As a potential accident scenario only hydrological scenario is taken into consideration, which is based on the influx of large amounts of precipitation, the cause of the largest number of accidents at industrial disposal sites. Analyses of environmental consequences, potential human losses and economic consequences are given. According to the risk matrix it is found that both of disposal sites are in the 'blue' zone of risk, which is interpreted as a tolerable level of risk, although the new disposal site is still in a better position than the old one because the expected level of risk is lower by one degree.

Information security risk analysis model using fuzzy decision theory

This paper proposes a risk analysis model for information security assessment, which identifies and evaluates the sequence of events – referred to as alternatives – in a potential accident scenario following the occurrence of an initiating event corresponding to abuses of Information Technology systems. In order to perform this evaluation, this work suggests the use of Event Tree Analysis combined with fuzzy decision theory. The contributions of the present proposal are: the development of a taxonomy of events and scenarios, the ranking of alternatives based on the criticality of the risk, considering financial losses, and finally, the provision of information regarding the causes of information system attacks of highest managerial relevance for organizations. We included an illustrative example regarding a data center aiming to illustrate the applicability of the proposed model. To assess its robustness, we analyzed twelve alternatives considering two different methods of setting probabilities of the occurrence of events. Results showed that deliberate external database services attack represent the most risky alternative.

Integrated risk assessment for multi-unit NPP sites—A comparison

Most of the nuclear power producing sites in the world houses multiple units. Such sites are faced with hazards generated from external events: earthquake, tsunami, flood, etc. and can threaten the safety of nuclear power plants. Further, risk from a multiple unit site and its impact on the public and environment was evident during the Fukushima nuclear disaster in March 2011. It is therefore important to evolve a methodology to systematically assess the risk from multi-unit site. For a single unit site, probabilistic risk assessment technique identifies the potential accident scenarios, their consequences, and estimates the core damage frequency that arise due to internal and external hazards. This challenging task becomes even more complex for a multiple unit site, especially when the external hazards that has the potential to generate one or more correlated hazards or a combination of non-correlated hazards are to be modelled. This paper presents an approach to evaluate risk for multiple NPP sites and also compare the risk for sites housing single, double and multiple nuclear plants.

WE‐G‐BRA‐07: Analyzing the Safety Implications of a Brachytherapy Process Improvement Project Utilizing a Novel System‐Theory‐Based Hazard‐Analysis Technique

Purpose:To investigate the hazards in cervical‐cancer HDR brachytherapy using a novel hazard‐analysis technique, System Theoretic Process Analysis (STPA). The applicability and benefit of STPA to the field of radiation oncology is demonstrated.Methods:We analyzed the tandem and ring HDR procedure through observations, discussions with physicists and physicians, and the use of a previously developed process map. Controllers and their respective control actions were identified and arranged into a hierarchical control model of the system, modeling the workflow from applicator insertion through initiating treatment delivery. We then used the STPA process to identify potentially unsafe control actions. Scenarios were then generated from the identified unsafe control actions and used to develop recommendations for system safety constraints.Results:10 controllers were identified and included in the final model. From these controllers 32 potentially unsafe control actions were identified, leading to more than 120 potential accident scenarios, including both clinical errors (e.g., using outdated imaging studies for planning), and managerial‐based incidents (e.g., unsafe equipment, budget, or staffing decisions). Constraints identified from those scenarios include common themes, such as the need for appropriate feedback to give the controllers an adequate mental model to maintain safe boundaries of operations. As an example, one finding was that the likelihood of the potential accident scenario of the applicator breaking during insertion might be reduced by establishing a feedback loop of equipment‐usage metrics and equipment‐failure reports to the management controller.Conclusion:The utility of STPA in analyzing system hazards in a clinical brachytherapy system was demonstrated. This technique, rooted in system theory, identified scenarios both technical/clinical and managerial in nature. These results suggest that STPA can be successfully used to analyze safety in brachytherapy and may prove to be an alternative to other hazard analysis techniques.

Safety barriers analysis of offshore drilling system by employing Fuzzy Event Tree Analysis

In technical systems like oil and gas drilling systems, an accident sequence starts with an Initiating Event (IE) and evolves over time through the interaction of barriers in terms of success or failure. As it has been dramatically demonstrated in a variety of cases, offshore oil rigs activities have severe consequences to people, asset, environment and reputation.A survey carried out on a leakage event in production phase. The barriers of the above IE are assessed by Event Tree Analysis (ETA) which evaluates the sequence of events in a potential accident scenario following the occurrence of an IE. In this research to calculate Failure Probability (FP) of barriers new approach is proposed. In this methodology, Reliability Block Diagram (RBD) and Fault Tree Analysis (FTA) are employed to quantify barriers FP. RBD is useful tool to quantify FP of barriers with logic diagram. FP of barriers with logic diagram is obtained by FTA. However it is often difficult to estimate precisely the FP of the components due to insufficient data. It has been reported that availability of the FP data pertaining to local conditions is surprisingly limited. In this study to overcome this problem using of expert judgment and then fuzzy logic is employed. Therefore, Fuzzy FTA (FFTA) is used to reduce uncertainty of expert judgment.

ICE layer growth on a cryogenic surface in a fusion reactor during a loss of water event

The design of fusion devices often includes water as primary coolant of the first wall/blanket system and a potential accident scenario is the steam/water injection from the primary circuit into the magnets' cryogenic chamber (cryostat). An important question to be answered for the above scenario is whether the pressure suppression created by the cryogenic surfaces is sufficient to prevent cryostat damage. The computer codes used for the assessment of ITER safety were validated in the past years against the EVITA (Experimental Vacuum Ingress Test Apparatus) experiment at CEA-Cadarache, which was designed for the simulation of the physical phenomena occurring during a coolant ingress into the cryostat, namely ice formation on a cryogenic structure, heat transfer coefficient between walls and fluid, flashing, two-phase critical flow. The paper presents the results obtained by the CONSEN computer program for seven post-test calculations of the EVITA facility relating to the cryogenic experiments carried out in 2004 and 2005, in which the kinetics of the ice layer formation was analysed. The comparison with the experimental data has been performed and the main agreements and differences are remarked.

Dynamic safety risk analysis of offshore drilling

The exploration and production of oil and gas involve the drilling of wells using either one or a combination of three drilling techniques based on drilling fluid density: conventional overbalanced drilling, managed pressure drilling and underbalanced drilling. The conventional overbalanced drilling involves drilling of wells with mud which exerts higher hydrostatic bottom-hole pressure than the formation pore pressure. Unlike the conventional overbalanced drilling, underbalanced drilling involves designing the hydrostatic pressure of the drilling fluid to be lower than the pore pressure of the formation being drilled. During circulation, the equivalent circulating density is used to determine the bottom-hole pressure conditions. Due to lower hydrostatic pressure, underbalanced drilling portends higher safety risk than its alternatives of conventional overbalanced drilling and managed pressure drilling. The safety risk includes frequent kicks from the well and subsequent blowout with potential threat to human, equipments and the environment.Safety assessment and efficient control of well is critical to ensure a safe drilling operation. Traditionally, safety assessment is done using static failure probabilities of drilling components which failed to represent a specific case. However, in this present study, a dynamic safety assessment approach for is presented. This approach is based on Bow-tie analysis and real time barriers failure probability assessment of offshore drilling operations involving subsurface Blowout Preventer. The Bow-tie model is used to represent the potential accident scenarios, their causes and the associated consequences. Real time predictive models for the failure probabilities of key barriers are developed and used in conducting dynamic risk assessment of the drilling operations. Using real time observed data, potential accident probabilities and associated risks are updated and used for safety assessment. This methodology can be integrated into a real time risk monitoring device for field application during drilling operations.

Exploring the limits of safety analysis in complex technological systems

From biotechnology to cyber-risks, most extreme technological risks cannot be reliably estimated from historical statistics. Therefore, engineers resort to predictive methods, such as fault/event trees in the framework of probabilistic safety assessment (PSA), which consists in developing models to identify triggering events, potential accident scenarios, and estimate their severity and frequency. However, even the best safety analysis struggles to account for evolving risks resulting from inter-connected networks and cascade effects. Taking nuclear risks as an example, the predicted plant-specific distribution of losses is found to be significantly underestimated when compared with available empirical records. Using a novel database of 99 events with losses larger than $50000 constructed by Sovacool, we document a robust power law distribution with tail exponent μ≈0.7. A simple cascade model suggests that the classification of the different possible safety regimes is intrinsically unstable in the presence of cascades. Additional continuous development and validation, making the best use of the experienced realized incidents, near misses and accidents, is urgently needed to address the existing known limitations of PSA when aiming at the estimation of total risks.

Safety of railway control systems: a new preliminary risk analysis approach

Preliminary risk analysis (PRA) is a methodology used in critical systems safety studies. It is primarily used at the preliminary stage of the system's design so as to determine the scenarios of potential accidents, to evaluate their probabilities of occurrence (frequency) as well as the severity of the resulting consequences and to propose solutions (preventive and/or mitigative safeguards) in order to reduce the risk level in terms of severity/occurrence (to reduce the frequency of the contributors or reduce the severity of the accident). The PRA was largely used in several industrial fields (aeronautics, weapons systems, chemistry, railways etc.) in order to study the safety of the systems. From one field to another, from one expert to another, many extremely different approaches and methods are used to carry out this analysis. Moreover, the formats representing the results of the PRA are often varied as well as the terminology and the concepts related to the PRA. The main goal of this paper, completed within the framework of the ANR-PREDIT-SECUGUIDE project (project financed by the National Agency for Research - France. It aims to study the impact of introducing the New Information and Communication Technologies (NICT) into railway systems safety) is to propose a PRA method and to determine standard contents of PRA to be used in the context of the railway control systems by taking into account the impact of NICT. Keywords automatic train control, feared events, new information and communication technologies Language: en

Quantitative risk analysis of offshore drilling operations: A Bayesian approach

Blowouts are among the most undesired and feared accidents during drilling operations. The dynamic nature of blowout accidents, resulting from both rapidly changing physical parameters and time-dependent failure of barriers, necessitates techniques capable of considering time dependencies and changes during the lifetime of a well. The present work is aimed at demonstrating the application of bow-tie and Bayesian network methods in conducting quantitative risk analysis of drilling operations. Considering the former method, fault trees and an event tree are developed for potential accident scenarios, and then combined to build a bow-tie model. In the latter method, first, individual Bayesian networks are developed for the accident scenarios and finally, an object-oriented Bayesian network is constructed by connecting these individual networks. The Bayesian network method provides greater value than the bow-tie model since it can consider common cause failures and conditional dependencies along with performing probability updating and sequential learning using accident precursors.

Dynamic Procedure for Atypical Scenarios Identification (DyPASI): A new systematic HAZID tool

The availability of a hazard identification methodology based on early warnings is a crucial factor in the identification of emerging risks. In the present study, a specific method named Dynamic Procedure for Atypical Scenarios Identification (DyPASI) was conceived as a development of bow-tie identification techniques. The main aim of the methodology is to provide a comprehensive hazard identification of the industrial process analysed, joined to a process of continuous improvement of the results of the assessment. DyPASI is a method for the continuous systematization of information from early signals of risk related to past events. The technique provides a support to the identification and assessment of atypical potential accident scenarios related to the substances, the equipment and the site considered, capturing available early warnings or risk notions. DyPASI features as a tool to support emerging risk management process, having the potentiality to contribute to an integrated approach aimed at breaking “vicious circles”, helping to trigger a gradual process of identification and assimilation of previously unrecognised atypical scenarios.

Surf's up: Safety through caution

THERE is an abundance of Web resources that delineate safety measures, debunk failure misconceptions, describe collaborative hazard reduction efforts, interpret diagnostic forensics, and advance best practices for thwarting fiascos. In addition to academic and government sites, there are private firms that have compiled noteworthy collections of open access research reports, technical manuals, and pragmatic engineering information. These digital libraries share many different document types including articles, book chapters, case studies, essays, images, reports, strategic plans, and theses. Many concentrate on present, past, and potential industrial accident scenarios. These serve to acquaint site visitors to mishaps that are possible when certain products, procedures, or processes are selected. They provide recommendations for accident avoidance and alert engineers, managers, and workers about the kinds of advanced training necessary for designing and operating devices associated with potentially hazardous systems. The following sites serve as examples of resources that promote precautionary steps to reduce failures.

Development of a risk-informed accident diagnosis and prognosis system to support severe accident management

RISARD, risk-informed severe accident risk diagnosis system, is a computerized tool developed to improve a severe accident management (SAM) for a nuclear power plant and to effectively support the MCR and the TSC in executing the relevant SAM activities. In order to provide a diagnostic capability to a state of the plant and a prognostic capability for an anticipated accident progression, the system examines (a) a symptom-based diagnosis of a plant damage state (PDS) sequence in a risk-informing way and (b) a PDS sequence-based prognosis of key plant parameter behavior, through a prepared database (DB) containing plant-specific severe accident risk (SAR)-related information. For a given accident, the replicated use of these two processes makes it possible to obtain information about the functional states of the plant and containment safety systems expected at the time of a severe accident as well as future trend of the key plant parameters that are essentially required for taking the relevant SAM action, eventually leading to an answer about the best strategy for SAM. The foregoing concept for an accident diagnosis and prognosis can give the SAM practitioners more time to take action for mitigating the consequences of the potential accident scenarios since they are made in a simple, fast, and efficient way through a prepared SAR database and it is useful especially when the plant information available for SAM is incomplete and limited. The main purpose of this paper is to (a) introduce the concept of the RISARD system proposed to support SAM and its implementation through a prepared OPR1000 plant- and MAAP code-specific SAR database and (b) assess prediction capabilities of major events expected during the evolution of a severe accident through the system.

Dynamic risk assessment using failure assessment and Bayesian theory

To ensure the safety of a process system, engineers use different methods to identify the potential hazards that may cause severe consequences. One of the most popular methods used is quantitative risk assessment (QRA) which quantifies the risk associated with a particular process activity. One of QRA's major disadvantages is its inability to update risk during the life of a process. As the process operates, abnormal events will result in incidents and near misses. These events are often called accident precursors. A conventional QRA process is unable to use the accident precursor information to revise the risk profile. To overcome this, a methodology has been proposed based on the work of Meel and Seider (2006). Similar to Meel and Seider (2006) work, this methodology uses Bayesian theory to update the likelihood of the event occurrence and also failure probability of the safety system. In this paper the proposed methodology is outlined and its application is demonstrated using a simple case study. First, potential accident scenarios are identified and represented in terms of an event tree, next, using the event tree and available failure data end-state probabilities are estimated. Subsequently, using the available accident precursor data, safety system failure likelihood and event tree end-state probabilities are revised. The methodology has been simulated using deterministic (point value) as well as probabilistic approach. This Methodology is applied to a case study demonstrating a storage tank containing highly hazardous chemicals. The comparison between conventional QRA and the results from dynamic failure assessment approach shows the significant deviation in system failure frequency throughout the life time of the process unit.