An intelligent system by fuzzy reliability algorithm in fault tree analysis for nuclear power plant probabilistic safety assessment

© Imperial College Press. Fault tree analysis for nuclear power plant probabilistic safety assessment is an intricate process. Personal computer-based software systems have therefore been developed to conduct this analysis. However, all existing fault tree analysis software systems only accept quantitative data to characterized basic event reliabilities. In real-world applications, basic event reliabilities may not be represented by quantitative data but by qualitative justifications. The motivation of this work is to develop an intelligent system by fuzzy reliability algorithm in fault tree analysis, which can accept not only quantitative data but also qualitative information to characterized reliabilities of basic events. In this paper, a newly-developed system called InFaTAS-NuSA is presented and its main features and capabilities are discussed. To benchmark the applicability of the intelligent concept implemented in InFaTAS-NuSA, a case study is performed and the analysis results are compared to the results obtained from a well-known fault tree analysis software package. The results confirm that the intelligent concept implemented in InFaTAS-NuSA can be very useful to complement conventional fault tree analysis software systems

An Object-Based Approach to Modelling and Analysis of Failure Properties

In protection systems, when traditional technology is replaced by software, the functionality and complexity of the system is likely to increase. The quantitative evidence normally provided for safety certification of traditional systems cannot be relied upon in software-based systems. Instead there is a need to provide qualitative evidence. As a basis for the required qualitative evidence, we propose an object-based approach that allows modelling of both the application and software domains. From the object class model of a system and a formal specification of the failure properties of its components, we generate a graph of failure propagation over object classes, which is then used to generate a graph in terms of object instances in order to conduct fault tree analysis. The model is validated by comparing the resulting minimal cut sets with those obtained from the fault tree analysis of the original system. The approach is illustrated on a case study based on a protection system from..

Modelling and Resolution of Dynamic Reliability Problems by the Coupling of Simulink and the Stochastic Hybrid Fault Tree Object Oriented (SHyFTOO) Library

Dependability assessment is one of the most important activities for the analysis of complex systems. Classical analysis techniques of safety, risk, and dependability, like Fault Tree Analysis or Reliability Block Diagrams, are easy to implement, but they estimate inaccurate dependability results due to their simplified hypotheses that assume the components’ malfunctions to be independent from each other and from the system working conditions. Recent contributions within the umbrella of Dynamic Probabilistic Risk Assessment have shown the potential to improve the accuracy of classical dependability analysis methods. Among them, Stochastic Hybrid Fault Tree Automaton (SHyFTA) is a promising methodology because it can combine a Dynamic Fault Tree model with the physics-based deterministic model of a system process, and it can generate dependability metrics along with performance indicators of the physical variables. This paper presents the Stochastic Hybrid Fault Tree Object Oriented (SHyFTOO), a Matlab® software library for the modelling and the resolution of a SHyFTA model. One of the novel features discussed in this contribution is the ease of coupling with a Matlab® Simulink model that facilitates the design of complex system dynamics. To demonstrate the utilization of this software library and the augmented capability of generating further dependability indicators, three di erent case studies are discussed and solved with a thorough description for the implementation of the corresponding SHyFTA models

DEVELOPMENT OF FAULT TREE ANALYSIS FOR COOLING WATER SYSTEM USING SPREADSHEET

Water is an essential substance in human life. From biological view, water helps us in continuing life on earth. In industrial application, water serves as medium in heat transfer for the industrial plant to survive its operation. Water is being used as it is the most abundant resource on earth. Continuation supply of cooled water throughout the plant’s operation help in maintaining the operational efficiency as equipment usage and functions are highly sensitive to the temperature and pressure of the raw material. Main function of cooling water in an industrial plant is to act as a medium for heat transfer to various raw materials, especially crude oil and processed chemical and petroleum. Failure in delivering ample and continuous amount of cooling water to the industrial plant may lead to more severe problem and total shutdown of the whole plant operation. In analyzing of such failure may happen, analyst use tools and software to find the possible causes and engineers can focus on creating a solution for such causes. By utilizing the spreadsheet, the author develops a template of Fault Tree Analysis, one of the available failure analysis tools complete with common statistical distributions. The author took a sample of Fault Tree Analysis of cooling water system from the Internet as a baseline and developed them using spreadsheet and lastly confirming the calculation using the BlockSim 8 software. The resulting Fault Tree Analysis is highly constricted by the size as increasing number of events in Fault Tree Analysis will change the formula that is already inserted by the author. Nevertheless, the result will serve as a guideline and baseline for future work in this field