Background and Objectives: Despite contribution to catastrophic accidents, human errors have been generally ignored in the design of human-machine (HM) systems and the determination of the level of automation (LOA). This paper aims to develop a method to estimate the level of automation in the early stage of the design phase considering both human and machine performance. Methods: A quantitative method is used to evaluate the performance of the whole human-machine system by the human-in-the-loop fault tree analysis while a qualitative and cross-sectional method is used to estimate human errors using the CREAM technique. The data are collected from real cases happened in the control room of the Ferdowsi power plant. Results: Full automatic option with an average error of 0. 013 had the lowest error rate, i. e. 1/8 of the error rate of the manual design. In addition, the CREAM analysis showed that the control room operators were not satisfied with the availability of procedures and Man-Machine Interface and operational support in general. Thus, on average, the reliability of the manual design is less than the reliability of the automatic setting. Conclusion: High machine reliability has led to the fact that the fully automatic design would be one of the best design choices for human-machine systems. However, based on the previous studies, high automation may have some humanout-of-the-loop shortcomings. Thus, this study proposed solutions to overcome these disadvantages based on the importance of the control parameters or the essence of human involvement in some decision-making and execution tasks.

In this paper, the reliability assessment based-on fault tree analysis in coherent multi-state emergency detection system in a sounding rocket is evaluated. A system was built with more complexity and containing various intersection terms. Analysis of such system whether by means of minimal cut-set or binary decision diagram (BDD) approaches requires complex analysis and will be time consuming owing to intersection terms. Also, the gained results have less accuracy and contain uncertainty. To overcome these problems a combinatorial method for solving static fault tree is used. This method combines minimal cut-set with BDD, and then computes the occurrence probability of top-event in fault tree. To fully demonstrate this method Emergency Detection system (EDS) is used as a case-study. Here, system analysis is done from a general approach. So assume that the overall system consists of two sub-systems: sending signal subsystem and cabin instrumental sub-system. Two different fault trees, one for each, are constructed and conclusions of analysis steps for multi-state systems consisting of multi-state elements are presented using fault tree analysis. Finally, by means of this method, the reliability assessed value of the system is estimated.

According to the rapid population growth and increasing need for clean and reliable water, wastewater treatment plants play an important role in providing a reliable source of water. In this regard, the reliability of a wastewater treatment plant is a critical issue while the effluent is reused or discharged to water resources. Main factors that affect the performance of a wastewater treatment plant are the variability of the influent, inherent variability in the treatment processes, deficiencies in design and mechanical equipments and operational failures. Thus, meeting established reuse and discharge criteria would require assessment of plant reliability. Amongst many techniques developed in system reliability analysis, Fault Tree Analysis (FTA) is one of the popular and efficient methods. FTA is a top down, deductive failure analysis in which an undesired state of a system, including failure to achieve system goals, is analyzed.The case study in this article is West Town wastewater treatment plant in Tehran which is a conventional activated sludge process and the effluent is used in irrigation of downstream green areas. The FTA components in this study include the violation of BOD from the standard limit for irrigation as the top event and cases such as operator fault, malfunction of the equipments and failure in the plant design as the basic events. The probabilities of basic events were determined based on available data and the experts’ and operators’ opinions and the probability of the top event was calculated. According to the obtained results, the probability of effluent BOD violation is estimated about 29% in which human error specially operator’s fault has the highest share in its occurance. Subsequently the mechanical, climate (influent wastewater quantity and quality) and factors related to collection network are placed in the following order. In this regard, to increase the reliability and management of the risk, some measures with the priority of focusing on reduction of human faults and incresing the level of supervision and inspection was recommended.

Fault Tree Analysis (FTA) as a Probabilistic Risk Assessment (PRA) method is used to identify basic causes leading to an undesired event, to represent logical relation of these basic causes in leading to the event, and finally to calculate the probability of occurrence of this event. To conduct a quantitative FTA, one needs a fault tree along with failure data of the Basic Events (BEs). Sometimes it is difficult to have an exact estimation of the failure rates of individual components or the probabilities of occurrence of undesired events due to a lack of sufficient data. Furthermore, due to imprecision in failure data of BEs, the overall result may be questionable. To avoid such conditions, a fuzzy approach may be used with the FTA technique. This reduces the ambiguity and imprecision arising from the subjectivity of data. Traditional FTA method needs a sound data base of failure of all BEs for quantifying the probability failure of system, whilst there is not such a database available in offshore pipeline industry, therefore, fuzzy FTA approach is proposed to deal with this issue. The proposed model is able to quantify the fault tree of offshore pipeline system in the absence or existence of data. This paper also illustrates with a case study the use of importance measures in sensitivity analysis.

In modern infrastructure, the demand for DC power-based appliances is rapidly increasing, and this phenomenon has created a positive impact on the acceptance of the DC microgrid. However, due to numerous issues such as the absence of zero crossing, bidirectional behaviour of sources, and different magnitudes of fault current during grid connected and islanded modes of operation, protecting DC microgrid remains a difficult task. Apart from these challenges, intermittent conditions are also a major challenge. Under such type scenarios, shadow conditions in the solar based DERs will reduce the desired output of the solar panels simultaneously in wind based DERs will be affected due to the low pressure of air. In this type of circumstances threshold setting based overcurrent relays may fail to sense the operational dynamics of the system. Therefore, in this manuscript, an ensemble of decision tree-based protection scheme is proposed to provide immunity against the stochastic conditions under the varying natures of the fault resistance. A total of 7150 test cases have been considered for validation of the protection scheme and all modules have been tested.

Background and Objective: Due to limited resources for risk reduction, prioritizing risks is crucial. Fault tree analysis (FTA) is one of the best-known methods, which faces uncertainty like other methods. On the other hand, despite its benefits and increasing use in industries, hydrogen poses significant risks. Given the lack of studies in the field of risk assessment of hydrogen tanks, this study aimed to develop a risk assessment method for a type of hydrogen tank. Materials and Methods: In this study, by using fuzzy logic, a connection was established between industrial experts and modern risk assessment methods,therefore, the uncertainty resulting from the lack of knowledge was mitigated as much as possible. Then, by transferring the fault tree to a Bayesian network, logical relationships between the system components were established, and obtaining updated probabilities became possible. By integrating fault tree analysis and these tools, the probability of fire and explosion in a hydrogen gasholder in one of Iran's industries was calculated. Results: The probability of fire and explosion was calculated to be 1. 147E-05. The presence of sufficient oxygen and an electrical spark, a delay in inspection, and an open flame were identified as the most influential basic events in causing this incident. Conclusion: While calculating the probability of an accident, the proposed method improves the effectiveness of risk control plans by identifying the most important basic events. It also provides a framework for examining new cases.