Purpose The purpose of this paper is to employ lessons learned from the industrial accidents in Skikda refinery during the period from 2005 to 2016 as input data for the numerical simulation of risk consequences to identify the exposed areas to the various effects of industrial accidents. Design/methodology/approach In order to assess how the lessons learned can contribute to modeling the accidents effects in the refining activities, this paper presents a combined statistical/dynamic approach that combines two main tools, namely, lessons learned from petroleum refining in Algeria and Areal Locations of Hazardous Atmospheres software. Findings The results showed that fire is the most frequent accident at Skikda refinery that is mainly caused by equipment failures with a frequent involvement of crude oil and LNG. The NO2 toxic effects are unacceptable. This means that in the case of a similar accident, the entire population will be exposed to an intolerable concentration of NO2. Therefore, people must be relocated to a safer place. The results indicate that the concentration threshold can be met beyond the distance of 1 km. Research limitations/implications Due to the economic importance of Skikda refinery and the absence of data related to the accidents in the refineries of Algiers, Arzew and Hassi Messaoud, this study is limited to the statistical analysis of accidents related to Skikda refinery. Practical implications This approach makes the risk assessment more practical and effective for the appropriate utilization of safety barriers and for the whole decision-making process. Originality/value This work presents a review paper of accidents that occurred in the oil-refining sector in Algeria, whose objective is learning lessons from past accidents history, by identifying their immediate causes and effects on personnel, equipment and environment in order to propose prevention measures. The novelty of this work is highlighted by the fact that this statistical analysis of oil and gas refining accident is realized for the first time in Algeria. This is due to the difficulty of obtaining data on accidents in the Algerian refining sector; for this reason, the authors have limited the study to the Skikda refinery.

The declination of the dependability requirements of the complex systems is one of the most critical processes of systems conception as well as systems engineering. We consider that these dependability requirements must be globally considered at the complete system level if they are to be respected before being allocated on the components of the system. Our approach is based on a three-dimensional decomposition model of the system whose purpose is to describe the way in which the system operates in order to deduce its dysfunction that serves as a basic support for the declination of the dependability requirements. The proposed method is applied to a nitric acid cooling system before being introduced into a chemical reactor.

This article describes how fault tolerance is an essential issue for many WSN (Wireless Sensor Network) applications such as wildlife monitoring, battlefield surveillance and health monitoring. It represents a great challenge for researchers regarding to the characteristics of sensor nodes which are prone to failures due essentially to their limited resources. Faults may occur, not only when sensor nodes exhaust their energy, but also when the congestion phenomenon emerges, because of a high traffic in the network and limited storage capacity of the sensor nodes. In order to support fault tolerance in WSNs, the authors propose a new scheme which incorporates a link quality estimation algorithm and a congestion detection mechanism to enable nodes that present high quality links to be chosen for routing in a non-congested area in case of faults. Evaluations through simulations under NS2 show that our proposed protocol tolerates faults with a minimum cost relatively to HEEP protocol and improves network’s performances comparatively to other fault tolerant protocols such as EF-LEACH.