As accidents were and still one of the main reasons standing behind the increasing rates of casualties such as death, injuries, and evacuations, the constant improvement of safety measures especially in the field of hydrocarbons remains a major concern. Therefore, in the work in hand, we attempt to shed the light on the ways of developing a method for the evaluation of risks of fire and explosions of pipelines. The causes of the latter and consequences are, in one hand, analyzed by means of fault tree and bow tie methods. On the other hand, a quantitative analysis implementing the Bayesian networks is used to estimate the probability of occurrence of the adverse event. Moreover, 72 basic events were found to be of the primary causes provoking the occurrence of undesirable events. However, some experts often find it difficult to precisely determine the probabilities of occurrence of basic events of the tree. For the purpose of evaluating the occurrence of each basic event, we used the fuzzy logic. Hence, at the end of the study, we were able to develop a model that could help us evaluate the risks accompanied the fires and pipelines explosion as well as the consequences.

<p><span lang="EN-US">This paper presents a fuzzy logic controller for maximum power point tracking (MPPT) in photovoltaic system with reduced number of rules instead of conventional 25 rules to make the system lighter which will improve the tracking speed and reduce the static error, engendering a global performance improvements. in this work the proposed system use the power variation and current variation as inputs to simplify the calculation, the introduced controller is connected to a conventional grid and simulated with MATLAB/SIMULINK. The simulation results shows a promising indication to adopt the introduced controller as an a good alternative  to traditional MPPT system for further practical applications</span></p>

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Dynamic Fault Tree (DFT) is suitable to capture functional and dynamic dependencies among events leading to system failure. There exist several approaches for analyzing DFTs, each of them suffers from drawbacks that limit its practical use. This paper presents a comprehensive methodology based on the structure function determination. It consists in performing both qualitative and quantitative analysis to establish failure sequences and to calculate the likelihood (probability and frequency) of dynamic systems failure. Failure sequences are extracted from the minimal canonical form of the top event and allow getting disjunctive failure sequences. From the quantitative point of view, the probability and frequency of any DFT top event are developed to make the proposed model able to quantify the failure probability and frequency of dynamic systems and the frequency of accident scenarios. The proposed procedure is applied on two benchmark examples: the first one is a safety‐related system while the second one is an accident scenario with dependent protection layers. In order to check the validity of the proposed method, the derived numerical results are compared with those obtained from Markov Chains models. © 2018 American Institute of Chemical Engineers Process Saf Prog 37: 535–552, 2018