Framework, approach and system of intelligent fault tree analysis for nuclear safety assessment

University of Technology, Sydney. Faculty of Engineering and Information Technology.Probabilistic safety assessment by fault tree analysis has been considered as an important tool to evaluate safety systems of nuclear power plants in the last two decades. However, since the estimation of failure probabilities of rare events with high consequences is the focus of this assessment, it is often very difficult to obtain component failure rates, which are specific to the nuclear power plant under evaluation. The motivation of this study is how to obtain basic event failure rates when basic events do not have historical failure data and expert subjective justifications, which are expressed in qualitative failure possibilities, are the only means to evaluate basic event failures. This thesis describes a new intelligent hybrid fault tree analysis framework to overcome the weaknesses of conventional fault tree analysis, qualitative failure possibilities and their corresponding mathematical representations to articulate nuclear event failure likelihoods, an area defuzzification technique to decode the membership functions of fuzzy sets representing nuclear event failure possibilities into nuclear event reliability scores, and a fuzzy reliability approach to generate nuclear event quantitative fuzzy failure rates from the corresponding qualitative failure possibilities subjectively evaluated by experts. Seven qualitative linguistic terms have been defined to represent nuclear event failure possibilities, i.e. very low, low, reasonably low, moderate, reasonably high, high, and very high and the corresponding mathematical forms are represented by triangular fuzzy numbers, which are defined in the [0, 1] universe of discourse based on nuclear event failure data documented in literatures using inductive reasoning. Finally, an intelligent software system called InFaTAS-NuSA, which has been developed to realize the new intelligence hybrid fault tree analysis framework to overcome the limitations of the existing fault tree analysis software systems by accepting both quantitative failure probabilities and qualitative failure possibilities, is also described in this thesis. The results of the InFaTAS-NuSA evaluation using a real world application confirm that InFaTAS-NuSA has yielded similar outputs as the outputs generated by a well-known fault tree analysis software system, i.e. SAPHIRE, and therefore it can overcome the limitation of the existing fault tree analysis software system, which can accept only quantitative failure probabilities. The experiment results also show that the fuzzy reliability approach seems to be a sound alternative for conventional reliability approach to deal with basic events which do not have historical failure data and expert subjective opinions are the only means to obtain their failure information

Reliability Analysis Approach For Operations Planning Of Hydropower Systems

Many existing hydropower storage facilities were built decades ago and components of these aging infrastructure facilities have higher risk of failure. Insufficient capacity or forced outages of the spillway and other waterway passage facilities during flooding incident could potentially increase the probability of dam safety incidents leading to public safety concerns. Currently approaches used to assess the risk and uncertainty in operational decision making are mainly based on qualitative assessment and expert judgment and can be significantly improved by the development of a framework that formally incorporates both qualitative and quantitative reliability analysis methods. Event tree analysis and fault tree analysis have traditionally been used in dam safety risk analysis, with results subject to data adequacy and availability. Our research shows that other methods, such as nonparametric analysis and Monte Carlo simulation techniques can yield good results as well. This study investigated the application of reliability analysis methods to existing hydropower storage facilities, with the objective of developing a new systems engineering based approach for risk and uncertainty analysis to assess and manage the risks of hydropower system operations. Our approach integrates reliability-based methods with hydro system optimization modeling to develop an operational reliability-based modeling framework and to formally treat risk and uncertainty in operations planning. This approach incorporates different sources of uncertainty that are typically encountered in operations planning of these systems, including failure probability of hydro system components such as non-power release structures and turbine facilities. This paper presents the framework we have developed and illustrates the application of our investigation for a hydropower system facility in British Columbia, Canada

Integrated Safety and Security Risk Assessment Methods: A Survey of Key Characteristics and Applications

Over the last years, we have seen several security incidents that compromised system safety, of which some caused physical harm to people. Meanwhile, various risk assessment methods have been developed that integrate safety and security, and these could help to address the corresponding threats by implementing suitable risk treatment plans. However, an overarching overview of these methods, systematizing the characteristics of such methods, is missing. In this paper, we conduct a systematic literature review, and identify 7 integrated safety and security risk assessment methods. We analyze these methods based on 5 different criteria, and identify key characteristics and applications. A key outcome is the distinction between sequential and non-sequential integration of safety and security, related to the order in which safety and security risks are assessed. This study provides a basis for developing more effective integrated safety and security risk assessment methods in the future

Assessing the reliability of adaptive power system protection schemes

Adaptive power system protection can be used to improve the performance of existing protection schemes under certain network conditions. However, their deployment in the field is impeded by their perceived inferior reliability compared to existing protection arrangements. Moreover, their validation can be problematic due to the perceived high likelihood of the occurrence of failure modes or incorrect setting selection with variable network conditions. Reliability (including risk assessment) is one of the decisive measures that can be used in the process of verifying adaptive protection scheme performance. This paper proposes a generic methodology for assessing the reliability of adaptive protection. The method involves the identification of initiating events and scenarios that lead to protection failures and quantification of the probability of the occurrence of each failure. A numerical example of the methodology for an adaptive distance protection scheme is provided

Timed Fault Tree Models of the China Yongwen Railway Accident

Safety is an essential requirement for railway transportation. There are many methods that have been developed to predict, prevent and mitigate accidents in this context. All of these methods have their own purpose and limitations. This paper presents a new useful analysis technique: timed fault tree analysis. This method extends traditional fault tree analysis with temporal events and fault characteristics. Timed Fault Trees (TFTs) can determine which faults need to be eliminated urgently, and it can also provide a safe time window to repair them. They can also be used to determine the time taken for railway maintenance requirements, and thereby improve maintenance efficiency, and reduce risks. In this paper, we present the features and functionality of a railway transportation system based on timed fault tree models. We demonstrate the applicability of our framework via a case study of the China Yongwen line railway accident

Risk analysis and reliability of the GERDA Experiment extraction and ventilation plant at Gran Sasso mountain underground laboratory of Italian National Institute for Nuclear Physics

The aim of this study is the risk analysis evaluation about argon release from the GERDA experiment in the Gran Sasso underground National Laboratories (LNGS) of the Italian National Institute for Nuclear Physics (INFN). The GERDA apparatus, located in Hall A of the LNGS, is a facility with germanium detectors located in a wide tank filled with about 70 m3 of cold liquefied argon. This cryo-tank sits in another water-filled tank (700 m3) at atmospheric pressure. In such cryogenic processes, the main cause of an accidental scenario is lacking insulation of the cryo-tank. A preliminary HazOp analysis has been carried out on the whole system. The risk assessment identified two possible top-events: explosion due to a Rapid Phase Transition - RPT and argon runaway evaporation. Risk analysis highlighted a higher probability of occurrence of the latter top event. To avoid emission in Hall A, the HazOp, Fault Tree and Event tree analyses of the cryogenic gas extraction and ventilation plant have been made. The failures related to the ventilation system are the main cause responsible for the occurrence. To improve the system reliability some corrective actions were proposed: the use of UPS and the upgrade of damper opening devices. Furthermore, the Human Reliability Analysis identified some operating and management improvements: action procedure optimization, alert warnings and staff training. The proposed model integrates the existing analysis techniques by applying the results to an atypical work environment and there are useful suggestions for improving the system reliability