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Liquefied petroleum gas (LPG) storage fires and explosions occur due to uncontrolled gas leaks and the gradual breakdown of associated safety barriers. By installing an effective safety barrier, these accidents can be greatly reduced. However, this study assesses the probability of failure of emergency safety barriers (ESBs) to help decision makers understand how they can support decisions to reduce the risks associated with LPG storage. In this context, an extension of the event tree analysis is proposed named emergency event tree analysis (EETA). The aim of this paper is to develop an integrated approach that uses interval type‐2 fuzzy sets and Analytic Hierarchy Process (AHP) method and emergency event tree analysis to handle uncertainty in the failure probability assessment of emergency safety barriers (ESBs). In addition, a case study on the failure probability assessment of the emergency safety barriers of the LPG plant in Algeria based on the proposed methodology is provided and carried out to illustrate its effectiveness and feasibility. The results demonstrated the ability of interval type‐2 fuzzy sets and the AHP method to provide highly reliable results and to evaluate the failure probability of emergency safety barriers in emergencies situations. However, the classical event tree analysis (CETA) does not take into account the possibility of assessing the emergency consequences of different accident scenarios. Consequently, it only allows you to estimate the occurrence probability of accident scenarios. The results of this study show that the value of the probability of failure of the emergency safety barriers can be used to estimate the probability of occurrence of emergency consequences under different accident scenarios, improved the reliability and help prioritize emergency improvement measures. The study provides scientific and operational references for analyzing emergency consequences of the various accident scenarios in all fields such as petrochemical, maritime industry, and health occupational. [ABSTRACT FROM AUTHOR]

IEC 61508 is a standard on design and operation of safety-instrumented systems (SISs) which has been adapted by many national regulations as the recommended way to achieve high-reliability systems. Many decisions about the design of SIS rely on the results from reliability assessments. It is therefore important that the reliability assessments are able to capture key properties of the system, such as the consideration of regular partial and full proof tests. IEC 61508 has proposed analytical formulas for commonly used architectures. Unfortunately, these formulas do not explicitly include the contribution of partial tests and consequently their use is mainly restricted to full proof tests. In addition, the already existing formulas dealing with partial tests disregard the different repair times. The aim of this paper is to (i) extend the PFD avg formulas given in IEC 61508 by including partial tests impact and, (ii) investigate their consistency based on multi-phase Markov models related to 1oo1 and 1oo2 architectures and (iii) to establish new generalized formulations in light of the results related to the investigation process, which account for the different repair times. Different comparisons are performed throughout the paper in order to validate the set of the derived formulations. [ABSTRACT FROM AUTHOR]

IEC 61508 standard provides a structured approach relying on hazards identification in order to establish safety requirements for safety instrumented systems (SISs). It aims at designing and operating the SIS within a reliability confidence that meets these requirements. The object of this paper is to give a concise description of IEC 61508 approach and to demonstrate it for the evaluation of safety barriers intervening against overpressure implemented on a butane storage tank. Specifically, the risk graph and layer of protection analysis approaches suggested in IEC 61508 for the determination of safety requirements are illustrated. In addition, it is shown that the use of more elaborate reliability approaches, such as fault tree and Markov graph, could be required for an effective risk assessment process. Actually, these approaches allow to consider the real configuration and operating conditions of the studied system. [ABSTRACT FROM AUTHOR]

The control of risks generated by modern industrial facilities could not be guaranteed without the use of safety instrumented systems (SIS). The failure of SIS to achieve their assigned functions could result in huge consequences with respect to both (i) the safety of the monitored system (relating to the SIS safety integrity) as well as (ii) its production availability due to false trips (relating to the SIS operational integrity). Furthermore, these two aspects are usually antagonistic. Therefore, the assurance of this double performance comes first by a thoughtful design of SIS. In that case, the aim of this paper is twofold. First, it focuses on the establishment of generic analytical formulations allowing the assessment of the SIS performance regarding safety integrity and operational integrity. Second, it deals with SIS architecture design optimization. The optimization problem is firstly addressed by a preliminary search for a balance between the above two quantities relying on the analysis of the structure of KooN architectures. Then, a more general and suitable approach based on genetic algorithms is proposed, where several performance indicators and the costs of purchase and maintenance are expected to be considered simultaneously. This general approach is illustrated through an application example. [ABSTRACT FROM AUTHOR]

Abstract: This paper is keeping with the topic of two papers which treated dynamic reliability problems and were presented in previous conferences. Its aim is to confirm the potentialities of a method which combines the high modeling ability of the piecewise deterministic processes and the great computing power inherent to the Monte Carlo simulation. This method is now applied to a simplified but realistic offshore oil production system which is a hybrid system combining continuous-time and discrete-time dynamics. The results thus obtained have been compared with those given by an ad hoc Petri net model for comparison and validation purposes. [Copyright &y& Elsevier]

The main objective of this paper is to provide a unified Markov model which could implement any parametric models devoted to the treatment of common cause failures (CCFs), namely: beta factor, multiple greek letter, alpha factor, multiple beta factor, and binomial failure rate. The choice of the Markovian representation is motivated by the fact that classical reliability approaches (e.g., Fault trees) are not able to catch the dynamic aspect induced by CCF events. The proposed Markovian model is also capable of dealing with any M-out-of- N configuration. It is illustrated on the basis of a system made up of four identical components ( N = 4) in order to quantitatively examine the differences between the first four mentioned parametric models. For that purpose, the considered performance indicators are the average unavailability ( U) and the average unconditional failure intensity (i.e., failure frequency) ( w). [ABSTRACT FROM AUTHOR]

• A new reliability method is proposed for practical engineering problems. • A novel combination between system theoretic process analysis (STPA) and stochastic petri nets (SPN) are applied. • The proposed method improves computational efficiency while ensuring the accuracy of results. • The accuracy and efficiency of the proposed method are proved. • The proposed method has strong applicability and is not limited by the type of problem. This paper investigates the ability to use complex multi-mobile robotic systems in risky and dynamic environments, such as industrial plants and laboratories, with the presence of the human factor. More specifically, it presents an approach to analyze the dominant risk, extract, model and quantify the hazard scenarios, then propose requirements using the combination between two methods: System Theoretic Process Analysis (STPA) and Stochastic Petri Nets (SPN). This approach is demonstrated with a case study related to a chemical transportation task within a miniature analysis laboratory in oil and gas industry. The main purposes of this article are: to investigate how the risk and safety of these systems should be managed, to create a framework for modeling collision hazard scenarios, further a Monte Carlo simulation is performed to quantify the collision frequency and unavailability. In addition, to generate the required constraints and requirements in order to improve the safe operation of robots within the laboratory. The novel contribution of this study is to provide a hazard assessment approach suited to multi-controller and autonomous systems while considering coordination between controllers. Hence, the current study proposes a set of safety requirements, which allow designers and programmers to improve autonomy features in mobile robots. The STPA-SPN combination offers better modeling and assessment of robot's performance as well as their hazard frequency. [ABSTRACT FROM AUTHOR]