On assessing importance of components in dysfunction urban systems given an earthquake: the case of Mt. Etna region

Mt Etna region (Sicily, Italy) is one of the test areas studied in the European Project “Urban disaster Prevention Strategies using MAcroseismic fields and FAult sources” ( UPStrat-MAFA) to which the methodology of Disruption Index (hereafter DI), recently developed to evaluate the dysfunction of urban systems caused by earthquakes (Ferreira et al., 2014), has been applied on a trial basis

SPURIOUS ACTIVATION ASSESSMENT OF THERMAL POWER PLANT’S SAFETY-INSTRUMENTED SYSTEMS

Safety-instrumented systems (also called technological protections) play the significant role in prevention and mitigating of major accidents that can occur on thermal power plant. Activations of safety-instrumented system turn the power unit into safe state by shutting it down or reducing it productivity. The power generation process operates continuously. Any unplanned outage of generation equipment leads to undersupply of energy and big commercial losses to generation company. In Russia the values of allowed spurious trip rate for safety-instrumented systems are set by regulatory agency. These values are strict to all technological protections and do not take into account the differences in amounts of losses. This paper presents more flexible approach based on the Farmer’s risk criterion. Also risk reduction factor for spurious activation is proposed

Application of Component Criticality Importance Measures in Design Scheme of Power Plants

This paper presents application of component criticality importance measures in phase of preparation and design of power plants. These measures provide a numerical rank to determine which components are more important for power plant reliability improvement or more critical for power plant failure. Identifying critical components for power plant reliability provides an important input for decision-making and guidance throughout the development project. The study on several schematic design options of conventional thermal power plant show that the importance measures can be used as an effective tool to assess component criticality in the project phase of new production capacities

Development and assessment of fire-related risk unavailability matrices to support the application of the maintenance rule in a PWR nuclear power plant

Two methods are presented which serve to incorporate the fire-related risk into the current practices in nuclear power plants with respect to the assessment of configurations. The development of these methods is restricted to the compulsory use of fire probabilistic safety assessment (PSA) models. The first method is a fire protection systems and key safety functions unavailability matrix which is developed to identify structures, systems, and components significant for fire-related risk. The second method is a fire zones and key safety functions (KSFs) fire risk matrix which is useful to identify fire zones which are candidates for risk management actions. Specific selection and quantification methodologies have been developed to obtain the matrices. The Monte Carlo method has been used to assess the uncertainty of the unavailability matrix. The analysis shows that the uncertainty is sufficiently bounded. The significant fire-related risk is localized in six KSF representative components and one fire protection system which should be included in the maintenance rule. The unavailability of fire protection systems does not significantly affect the risk. The fire risk matrix identifies the fire zones that contribute the most to the fire-related risk. These zones belong to the control building and electric penetrations building.Peer ReviewedPostprint (published version

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk, and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results, and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods, such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty, are rendered obsolete, since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods. This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper describes how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components

A novel application of system survival signature in supply chain risk management

Supply chains have become complex because of the globalization and outsourcing, and the lack of visibility across the entire network makes it difficult to manage the risks. The concept of 'System survival signature' has recently been developed for capturing the network configuration of a system comprising different types of components. Its utilization in the evaluation of system reliability is unique in terms of its capability of segregating the network signature from the probability distribution of failure time of components. We introduce this concept in the realm of supply chain risk management. This novel application can be helpful in evaluating supply network reliability through gauging two distinct features of network configuration and risk profiles of the suppliers. The application is illustrated with the help of two simple examples. The technique can be of significant value to the supply chain managers in taking strategic decisions concerning suppliers and network configuration. We have also adapted the existing risk importance measures in the field of reliability engineering for their application in the domain of supply network reliability

Probabilistic safety assessment-based importance analysis of cyber-attacks on nuclear power plants

With the application of digital technology to safety-critical infrastructures, cyber-attacks have emerged as one of the new dangerous threats. In safety-critical infrastructures such as a nuclear power plant (NPP), a cyber-attack could have serious consequences by initiating dangerous events or rendering important safety systems unavailable. Since a cyber-attack is conducted intentionally, numerous possible cases should be considered for developing a cyber security system, such as the attack paths, methods, and potential target systems. Therefore, prior to developing a risk-informed cyber security strategy, the importance of cyber-attacks and significant critical digital assets (CDAs) should be analyzed. In this work, an importance analysis method for cyber-attacks on an NPP was proposed using the probabilistic safety assessment (PSA) method. To develop an importance analysis framework for cyber-attacks, possible cyber-attacks were identified with failure modes, and a PSA model for cyber-attacks was developed. For case studies, the quantitative evaluations of cyber-attack scenarios were performed using the proposed method. By using quantitative importance of cyber-attacks and identifying significant CDAs that must be defended against cyber-attacks, it is possible to develop an efficient and reliable defense strategy against cyber-attacks on NPPs

Risk-informed approach to the safety improvement of the reactor protection system of the AGN-201K research reactor

Periodic safety reviews (PSRs) are conducted on operating nuclear power plants (NPPs) and have been mandated also for research reactors in Korea, in response to the Fukushima accident. One safety review tool, the probabilistic safety assessment (PSA), aims to identify weaknesses in the design and operation of the research reactor, and to evaluate and compare possible safety improvements. However, the PSA for research reactors is difficult due to scarce data availability. An important element in the analysis of research reactors is the reactor protection system (RPS), with its functionality and importance. In this view, we consider that of the AGN-201K, a zero-power reactor without forced decay heat removal systems, to demonstrate a risk-informed safety improvement study. By incorporating risk- and safety-significance importance measures, and sensitivity and uncertainty analyses, the proposed method identifies critical components in the RPS reliability model, systematically proposes potential safety improvements and ranks them to assist in the decision-making process. Keywords: Research reactor, Reactor protection system, Probabilistic safety assessment, Risk-informed design, Unavailability analysis, Sensitivity analysi

Efficient Global Sensitivity Analysis of Structural Vibration for a Nuclear Reactor System Subject to Nonstationary Loading

The structures associated with the nuclear steam supply system (NSSS) of a pressurized water reactor (PWR) include significant epistemic and aleatory uncertainties in the physical parameters, while also being subject to various non-stationary stochastic loading conditions over the life of a nuclear power plant. To understand the influence of these uncertainties on nuclear reactor systems, sensitivity analysis must be performed. This work evaluates computational design of experiment strategies, which execute a nuclear reactor equipment system finite element model to train and verify Gaussian Process (GP) surrogate models. The surrogate models are then used to perform both global and local sensitivity analyses. The significance of the sensitivity analysis for efficient modeling and simulation of nuclear reactor stochastic dynamics is discussed

A fuzzy Bayesian network approach for risk analysis in process industries

YesFault tree analysis is a widely used method of risk assessment in process industries. However, the classical fault tree approach has its own limitations such as the inability to deal with uncertain failure data and to consider statistical dependence among the failure events. In this paper, we propose a comprehensive framework for the risk assessment in process industries under the conditions of uncertainty and statistical dependency of events. The proposed approach makes the use of expert knowledge and fuzzy set theory for handling the uncertainty in the failure data and employs the Bayesian network modeling for capturing dependency among the events and for a robust probabilistic reasoning in the conditions of uncertainty. The effectiveness of the approach was demonstrated by performing risk assessment in an ethylene transportation line unit in an ethylene oxide (EO) production plant