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A Comparative Study of STPA Hierarchical Structures in Risk Analysis: The case of a Complex Multi-Robot Mobile System
(Hal open science journal.Volume 18, 2019.pp 163-174, 2019-01-01) Zennir Youcef; Bensaci Chaima
Autonomous multi-robot systems are among the most complex systems to control, especially when those robots navigate in fully hazardous and dynamic environments such as chemical analysis laboratories which include dangerous and harmful products (poisonous, flammable, explosive...). This paper presents an approach for systems-complex and theoretic safety assessment, also it considers their coordinating, cooperating and collaborating using different control architectures (centralized, hierarchical and modified hierarchical). We classified at first those control architectures according to their properties using Bowtie analysis method, and then we used a systems-theoretic hazard analysis technique (STPA) to identify the potential safety hazard scenarios and their causal factors .
A New Approach to System Safety of humanmulti-robot mobile system control with STPA and FTA
(ALGERIAN JOURNAL OF SIGNALS AND SYSTEMS (AJSS). Vol. 5, Issue 1.pp79-85, 2020-03-01) Bensaci Chaima; Zennir Youcef
Autonomous Mobile multi-robots are among the most complex systems in their control. Especially when those robots navigate in hazardous and dynamic environments such as chemical analysis laboratories which include dangerous and harmful products (poisonous, flammable, explosive ...). This study deals the safety problem in a robotic analysis laboratory and investigates the possibility to use those autonomous multirobots in such environments with the presence of human workers without serious hazards. We used a systems-theoretic hazard analysis technique (STPA) in addition to fault tree analysis to identify the potential safety hazard scenarios, their causal factors and we conclude by a set of recommendations.
A New Information-Based Heuristic for Distributed DDoS Detection and Mitigation: Distributed and Collaborative DDoS Detection
(International Journal of Organizational and Collective Intelligence Volume 12 • Issue 4, 2022) Nafir , Abdenacer; Mazouzi , Smaine; Chikhi ,Salim
In this paper a novel collective method for DDoS detection is introduced. The method is distributed and implemented as a multi-agent system, and where local decision is based on an informationbased heuristic, namely the entropy. According the calculated entropy a router exchange data with its neighbors aiming at collectively decide if a DDoS is ongoing or not. Most of the works of the literature that are based on the entropy they have used source addresses. The authors’ method is based on the entropy of the distances traveled by the packets, so spoofing IP packets will be hard to perform by hackers. Each router combines its decision with those of its neighbors. Such a collective detection allows to apply defense against the attack despite the victim is out of service or cannot perform DDoS mitigation because the traffic is congested in its neighborhood. Conducted experiments using the platform OMNet++ show the potential of the new method for efficient collaborative and distributed detection and mitigation of DDoS attacks.
A new tool for risk analysis and assessment in petrochemical plants
(Alexandria University. Alexandria Engineering Journal.2016.55,pp2919-2931, 2016-06-09) Mechhoud El-Arkam ; ;
The aim of our work was the implementation of a new automated tool dedicated to risk analysis and assessment in petrochemical plants, based on a combination of two analysis methods: HAZOP (HAZard and OPerability) and FMEA (Failure Mode and Effect Analysis). Assessment of accident scenarios is also considered. The principal advantage of the two analysis methods is to speed-up hazard identification and risk assessment and forecast the nature and impact of such acci- dents. Plant parameters are analyzed under a graphical interface to facilitate the exploitation of our developed approach. This automated analysis brings out the different deviations of the operating parameters of any system in the plant. Possible causes of these deviations, their consequences and preventive actions are identified. The result is risk minimization and dependability enhance- ment of the considered system. 2016 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
A systematic approach for risk assessment in LPG storage tanks area – SKIKDA refinery.
(Algerian Journal of Environmental Science and Technology. Vol.X. NoX. (YYYY), 2021-05-17) ; Mechhoud El-Arkam; ; Zennir Youcef
In this work we present a risk assessment methodology, Implemented based on the integration of two methods D-HIGRAPH and HAZOP. The approach is applied on the LPG storage Area in SKIKDA refinery (the most important refinery in Algeria). Several recommendations raised from the study to improve the plant safety. The study is completed by simulating the effects resulted from an explosion in the sphere S-151 (for butane storage) using ALOHA Software. In simulation, the following cases are considered: the explosion effect, the toxic material release and the thermal effect of flammable material release, the results are mapped on the refinery map to indicate the exact threated zones
A Techno-Economic Study of a Hybrid PV-Wind-Diesel Stand-Alone Power System for a Rural Telecommunication Station in Northeast Algeria †
(Engineering proceedings, 2023-10-27) Zegueur Ahlem; Sebbagh Toufik; Metatla Abderrezak
Telecommunication stations, particularly operating in rural areas are usually powered by diesel generators due to the lack of access to the utility grid. However, the growing cost of energy due to the constantly increasing fuel prices and the related greenhouse gas emissions contributing to the global warming have driven the telecom companies to seek for better energy management solutions. In this paper, we study the economic feasibility of an environmentally friendly power supply system for rural telecommunication station in the city of Skikda, northeast Algeria. The proposed system is a standalone hybrid PV-Wind system with pre-existing diesel generators and battery storage. Different system configurations are considered in the study: (a) Diesel generators only, (b) PV-Diesel-battery, (c) Wind-Diesel-Battery, (d) PV-Wind-Diesel-Battery, and lastly (d) PV-WindBattery, this helps to select the most optimal solution based on the lowest net present cost (NPC) and the cost of energy (COE) of each configuration. The optimization is performed using HOMER PRO software. The results showed that a hybrid system of 5 kW DG, 3.81 kW of PV capacity, 3 wind turbines and 14 battery bank is the best design for the proposed power system with an NPC of 85,673 $ and a COE of 0.214 $. The greenhouse gas emissions were considerably reduced to more than half making the proposed system a technically, economically and environmentally viable solution.
Activated Carbon Supported Cobalt as Efficiency Adsorbent: Application Chemical Agricultural pollutant 2,4-D Herbicide Removal from Aqueous Solution
(ORIENTAL JOURNAL OF CHEMISTRY, 2017-09-07) BOUGHAITA IMEN; BOUCHELTA CHAFIA; MEDJRAM MOHAMED SALAH; PIERRE MAGRI
In this work, an activated carbon derived from date pits and stems (DPSAC) was prepared by physical activation under N2 and used as a support of cobalt transition metals, by wetness impregnation at different Co content and different calcination temperatures. The optimal operator conditions were 20 wt% cobalt impregnation ratio and 300°C calcination temperature. The grafted material was characterized by methods: thermo gravimetric analysis (TGA), scanning electron microscopy (SEM), Fourier transform of infrared spectroscopy (FTIR). The activated carbon (DPSAC) and grafted activated carbon (Co/DPSAC) were realized on adsorption of 2,4- dichlorophenoxyacetic acid (2,4-D) from aqueous solution , it was found that the cobalt-grafted dates pits and stems activated carbon promoted the 2,4-D adsorption kinetics, The Langmuir and Freundlich isotherms models were applied for the adsorption results. The rate of adsorption of 2,4- D onto (DPSAC) and (Co/DPSAC) were estimated and described using a pseudo-second order model.
Adaptive Sliding Mode Control Improved by Fuzzy-PI Controller: Applied to Magnetic Levitation System †
(Journal Engineering Proceedings.. 2022, 14, 14. https://doi.org/10.3390/engproc2022014014.pp 01-09, 2022-02-08) ; Zennir Youcef
This study mainly concerns the use of Fuzzy-PI adaptive sliding control (Fuzzy-ASMC) to force the stat space of MAGLEV to track a desired trajectory. The usage of adaptive sliding mode control allows the MAGLEV to operate in an uncertain environment and in the presence of external disturbances. The Fuzzy-PI schema is designed to improve the performance of adaptive sliding mode control and reduce the main drawback caused by the discontinuous term of this method, which is the well-known chattering phenomenon. The results of our study prove the effectiveness of the proposed approach in achieving desired performances
An Intelligent Optimization Algorithm for Scheduling the Required SIL Using Neural Network †
(Journal Engineering Proceedings.Eng. Proc. 2023, 29, 5. https://doi.org/10.3390/engproc2023029005.pp 1-10., 2023-01-11) ; ; Zennir Youcef
The purpose of safety analysis is to ensure that hazards and risks that could be a possible source of harm and damage are reduced well enough by dealing with all phases of the safety lifecycle and design of suitable safety barriers. It is known that any error or failure to perform the function of each proposed safety barrier can cause extreme damage to the environment, facilities and humans, and even loss of life. Therefore, it is necessary to ensure the effectiveness of the study or analysis. However, even with the major development in control system fields the problems of uncertainties, classification and optimization are still considered unsolved issues. In recent years several tools are developed based on artificial intelligence to deal with such difficulties. In this work, an approach based on Artificial Neural Networks (ANN) is developed to schedule the SIL values of the safety integrity functions (SIF) of an industrial-fired heater. The SIFs are first deduced from HAZOP study for the fired heater. The SIL risk of the consequences related to personnel health and safety, the economic SIL and environment SIL are considered as inputs of the multilayer network with a predefined hard limit activation function.
Analyzing Storage Tank Incidents: Utilizing Fishbone Diagram and Fault Tree Methods
(International Journal of Automation and Safety (IJAS). Vol.02, N°: 0.pp 47-56, 2024-06-30) Zennir Youcef
Oil and gas are the most important energies in the word. To exploit them both, go through a set of steps such as exploration; drilling, extraction, refining and storage. In this last step (storage), there are several methods of storage using floating Roof Tanks, Fixed Roof Tanks, Fixed Roof Tanks with internal floating Roof, Sphere…. etc. In storage phase happen many accidents and incidents. This paper divided in two main parts, the first part reviews storage tank types, storage tanks accidents types and accident locations. And in the second parts we used Fish bone Diagram (Ishikawa Diagram) and Fault tree method to investigate the causes of storage tanks accidents/incidents and their mitigation action. The statical analysis of the accident shows that 74%of accident happened between refinery facilities and the most common accidents are Fire and Explosion by 80%. While the most two major causes of accidents are Lightning by 33%, followed by human Error by 30%
Application of multilayer perceptron network and random forest models for modelling the adsorption of chlorobenzene on a modifed bentonite by intercalation with hexadecyltrimethyl ammonium (HDTMA)
(Reaction Kinetics, Mechanisms and Catalysis, 2021-11-19) Nabil Bougdah; Salim Bousba; Youghourta Belhocine; Nabil Messikh
Prediction of adsorption capacity, one of the most important properties of any adsorbent-adsorbate system, is crucial for adsorption studies. In this investigation, two approaches such as multilayer perceptron (MLP) and random forest (RF) were used to predict the adsorption capacity of hexadecyltrimethyl ammonium modifed bentonite to remove chlorobenzene (CB) from aqueous solution. The adsorption study was conducted in batch mode at diferent adsorption parameters. The results show that the adsorption processes were best described by Freundlich isotherm model, while the adsorption mechanism followed the pseudo-second order kinetics. It was observed that the structure of MLP model that give the best prediction consisted of three layers: input layer with four neurons, output layer with one neuron, and four neurons at hidden layer. The three important parameters for RF model were ntree=500, mtry=1, and node size=1. According to the results obtained, the MLP model provided slightly higher levels of accuracy with a consistently high coefcient of determination (R2=0.996) and low root mean square error (RMSE=0.00101) compared to RF model. (R2=0.969, RMSE=0.03008). Therefore, the initial concentration of CB with 35.29%, appeared to be the most infuential parameter in the adsorption of CB on the modifed bentonite.
Application of STPA for Comprehensive Risk Analysis of Naphtha Explosion Hazards Case study: Column C-63 at Skikda-RA1K refinery
(ALGERIAN JOURNAL OF SIGNALS AND SYSTEMS (AJSS).Vol. 9, Issue 3.pp153-161, 2024-09-30) Zennir Youcef
Chemical accidents always result in significant losses due to the flammable, explosive, and toxic characteristics of hazardous chemicals. Analysis of process safety parameters is an effective way to prevent hazardous chemical accidents and reduce losses. System-theoretic process analysis (STPA) is a newer hazard analysis technique that is based on systems theory. It has been shown to be effective in identifying hazards in other industries, but its application in oil and gas plants is still rare and limited due to systems complexities and other challenges. This paper aims to apply the STPA method to a complex system “column C-63” at the Skikda RA1K refinery to prevent the explosion scenario of naphtha. The results show that STPA was able to identify the root causes of the explosion scenario, which is important for preventing chemical risks.
Approche distribuée de l'apprentissage : Application au contrôle de la trajectoire d'un robot hexapode
(Journal Européen des Systèmes Automatisés. Volume 39- n°8. pp 965-993, 2005-10-01) Zennir Youcef
Une approche distribuée de l’apprentissage par renforcement de type Q-learning est proposée dans laquelle des groupes d’agents contribuant à une même tâche mènent leur apprentissage en tenant compte ou non de l’existence des autres agents. L’approche est appliquée à la commande d’un robot hexapode pour qu’il apprenne à marcher et à changer de trajectoire tout en contrôlant sa posture. Les résultats de simulation valident l’approche proposée. D’autres travaux de recherche relatifs au domaine sont discutés.
Automated depandability analysis of the HDPE Reactor using D-higraphs HAZOP assistant
(ALGERIAN JOURNAL OF SIGNALS AND SYSTEMS (AJSS). Vol. 2, Issue 4.pp 255-265, 2017-12-01) Mechhoud El-Arkam; Zennir Youcef
In this paper we present a HAZOP Assistant based on D-higraphs and dedicated to a functional modeling technique that gathers functional and structural information of the process under study. This work is applied to the study of an industrial case - High Density Polyethylene reactor part of the CP2K plant situated in the petrochemical platform of Skikda- and its results are compared with the conventional HAZOP study and SADT method.
Autonomous Obstacle Avoidance for a Hexapod Robot Using Proximity Sensors
(international Journal of Automation and Safety (IJAS)Vol.02, N°: 01.pp 01-06, 2024-06-30) Zennir Youcef
The hexapod walking robot serves as a versatile mobile platform, adept at navigating challenging terrains owing to its stable leg-based locomotion. Demonstrating high stability in both static and dynamic states, it effectively traverses terrains with obstacles. In this paper, we propose a method for obstacle avoidance utilizing proximity sensors, integrated with an Intelligent Walking Algorithm (IWA) for locomotion control, and a tripod gait algorithm for walking. Our simulations were conducted using the CoppeliaSim simulator with the Python interface. The results were highly satisfactory, as the robot consistently avoided obstacles with a remarkable combination of stability and precision.
Comparative Study of STPA and Bowtie Methods: Case of Hazard Identification for Pipeline Transportation
(Journal of Failure Analysis and Prevention, 2020-10-09) Wafia Benhamlaoui; Mounira Rouainia; Yiliu Liu; Mohammed Salah Medjram
In this research, two methods, the STPA and Bowtie, were applied to realize a hazard identification on pipeline transportation, more precisely a condensate pipeline, in SKIKDA region. This identification was followed by a comparison of the results obtained previously, with respect to some aspects; we compared all hazards identified by both methods and classified them into categories, also comparing consequences and losses; we also compared the different steps of each method used. The study performed allows us to determine the main differences using the STPA and Bowtie methods for hazard identification on pipeline transport and highlights a complementary while using them in order to identify in a more exhaustive way the hazards associated with the system being studied. Their combination may be more useful for a thorough hazard identification.
Control Of Mobile Robot Navigation Under The Virtual World Matlab-Gazebo
(ALGERIAN JOURNAL OF SIGNALS AND SYSTEMS (AJSS) .Vol. 2, Issue 4.pp 207-217, 2017-12-01) Zennir Youcef Bensaci Chaima
In this paper, we present our navigation control approach of a mobile robot (Turtlebot 2 robot) based on the stability Lyapunov function; our mobile robot is composed of two differential wheels. The kinematic model of the robot is presented followed by the description of the control approach. A 3D simulation under the Gazebo software is developed in interaction with the kinematic model and the control approach under MATLAB-SIMULINK software. The purpose of this study is to carry out an autonomous navigation; we initially planned different trajectories then we tried to be followed them by the robot. Our navigation strategy based on its odometry information, based on robot position and orientation errors; Velocity commands are sent for the robot to follow the chosen path. Different simulations were performed in 2D and 3D and the results obtained are presented followed by the envisaged future work.
Cost and Risk Prediction in Road Transportation of Hazmat by ANFIS Trained with PSO, FA, HBBO and ICA
(International Journal of Safety and Security Engineering.Vol. 12, No. 4, August, 2022, pp. 429-439, 2022-08-01) ; Zennir Youcef;
This paper proposes adaptive neuro-fuzzy inference system (ANFIS) to predict the risk with its aggregated cost (CR) of an accident in road transportation of hazardous material, the aim is to provide a more accurate and reliable data for the safety of transportation. The determination risk index by the conventional methods such as Risk graphs and deterministic approaches may lead to imprecise values due to the uncertainties, in both parameters and models. The proposed technique is a hybrid schema, which combines the main advantageous of fuzzy logic (address uncertainties) and neural network (learn from a given data). In other hand our study seeks to tune the parameters of the proposed model by particle swarm optimization (PSO), firefly algorithm (FA), imperialist competitive algorithm (ICA) and human based-behavior optimization (HBBO) and hence optimize the performance of ANFIS. The simulation result of this work and the comparative analysis shows that ANFIS yield height performance and the ANFIS-PSO was the outstanding one in the training phase, while ANFIS-FA gives better results in the testing process.
Cost Effective Analysis of the Design of Safety Instrumented Systems Using Manta-Ray Foraging Optimization Algorithm
(International Journal of Safety and Security Engineering Vol. 13, No. 6, December, 2023, pp. 975-986, 2023-12-25) Innal Fares
This study aims to develop a new cost effectiveness analysis framework in the context of safety instrumented systems (SIS) design and operation. The primary objective is to achieve an optimal equilibrium among safety integrity, operational integrity, and lifecycle cost of SIS. It is essential to note that these objectives may often be in conflict; for instance, enhancing safety integrity could potentially diminish operational integrity and escalate costs. Achieving this balance is crucial to ensure that the risk level being addressed aligns precisely with the desired objectives while minimizing any adverse effects. The novelty of this paper lies in the refined formulation of a multi-objective optimization problem and the application of a recently developed swarm-based MantaRay Foraging Optimization (MRFO) algorithm. The effectiveness of this approach is demonstrated through a typical SIS design challenge, which entails satisfying specific measures in terms of Safety Integrity Level (SIL), spurious trip activation rate, and lifecycle cost. These measures depend on variables such as the number and voting scheme of components, their types, and the intervals for potential proof tests. For validation and comparison, the problem was initially tackled using a conventional approach based on genetic algorithms. Subsequently, the MRFO algorithm was employed, yielding highly satisfactory results and confirming its proficiency in resolving real-world SIS optimization challenges. Notably, the MRFO algorithm produced a greater number of solutions compared to the genetic algorithm approach. This increase in solution options is advantageous, offering decision-makers a broader array of choices for optimal system design. This study contributes significantly to the field of SIS design, presenting an innovative, algorithm-driven approach to balancing safety, operational integrity, and cost in system development. It also contributes to understanding the life cycle costs of security barriers in general.
Deep Q-Learning-Based Trajectory Optimization for Vehicle Navigation in CARLA
(ALGERIAN JOURNAL OF SIGNALS AND SYSTEMS (AJSS).Vol. 9, Issue 2.pp 128-133, 2024-06-01) Zennir Youcef
This paper presents a comprehensive study that focuses on simulating a vehicle within the autonomousvehicle simulator, CARLA. The primary objective of this research is to enable the vehicle to accurately follow apredetermined trajectory while effectively avoiding obstacles in its environment. Deep QLearning algorithms areemployed to achieve this goal, aiming to optimize the safety of the vehicle'snavigation. The simulation of the vehicleserves as a platform for studying the rules of Deep Q-Networks (DQN) and their impact on the vehicle's navigation.The objective is to identify the most suitable rule that leads to improved optimization of the vehicle's trajectory. Byleveraging the capabilities of CARLA as the simulation environment and implementing state-of-the-art DQNalgorithms, this research contributes to the advancement of autonomous vehicle technology. The findings of this studyhave practical implications for enhancing the safety and efficiency of autonomous vehicle navigation systems, makingthem highly relevant to industryprofessionals, researchers, and academic scholars in this field.

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