Faculté de Technologie

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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.
Extracts of Ruta Chalepensis as Green Corrosion Inhibitor for Copper CDA 110 in 3% NaCl Medium: Experimental and Theoretical Studies
(Analytical &Bioanalytical Electrochemistry, 2019-07-03) N. Ammouchi; H. Allal; E. Zouaoui; K. Dob
he corrosion inhibition of copper CDA 110 in 3% NaCl by Ruta Chalepensis’ extract is studied by using electrochemical stationary and non-stationary methods. The obtained results reveal a significant enhancement of the inhibition efficiency by increasing the extract concentration. The adsorption behavior is found to obey Langmuir isotherm. Polarization study shows a cathodic character for the green leaves. The increase of medium temperature accelerates the corrosion process. The values of activation energy and thermodynamic parameters are calculated. In-depth the first principles calculations based on density functional density have been performed in order to evaluate the electronic structure and to understand the corrosion mechanism
Sensorless Predictive Direct Power Control PDPC-SVM For PWM Converter Under Different Input Voltage Conditions
(Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 2020-03-26) Ismail Boukhechem; Ahcen Boukadoum; Lahcene Boukelkoul; Houssam Eddine Medouce
In this paper, a new virtual flux (VF) based predictive direct power control (VF-PDPC) applied for a three-phase pulse width modulation (PWM) rectifier is proposed. The virtual flux estimation is performed using a pure integrator in series with a new adaptive algorithm in order to cancel dc offset and harmonic distortions in the estimated VF. The introduced structure is able to produce two virtual flux positive sequence components orthogonal output signals under unbalanced and distorted voltage conditions. The main features of the proposed virtual flux estimator are, it's a simple structure, accuracy, and fast VF estimation over the excited integrators. Therefore, the estimated VF is then used for robust sensorless VF-PDPC with a constant switching frequency using space vector modulation (SVM) and tested through numerical simulations. The instantaneous active and reactive powers provided by orthogonal VF positive sequence components are directly controlled. More importantly, this configuration gives quasi-sinusoidal and balanced current under different input voltage conditions without using the power compensation methods. The results of the simulation confirmed the validity of the proposed virtual flux algorithm and demonstrated excellent performance under different input voltage conditions, a complete rejection of disturbances.
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.
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.
Increment of heat transfer by graphene-oxide and molybdenum-disulfide nanoparticles in ethylene glycol solution as working nanofluid in penetrable moveable longitudinal fin
(Waves in Random and Complex Media, 2022-01-31) Talbi Nabil; Kezzar Mohamed; Malaver Manuel; Tabet Ismail
The main interest of the current research study is, on the one hand, to increase heat transfer of the base and mixture fluids by using hybrid nanoparticles. By considering two types of boundary conditions such as insulated and convective tips, to explore numerically and analytically the simultaneous impacts of the thermal radiative and free convective flow of hybrid nanofluid via a moving porous longitudinal fin. This investigation employs Darcy’s model and the mixture base fluid H2O (50%)–C2H6O2 (50%). The governing equations have been solved by utilizing Runge–Kutta–Fehlberg 4th–5th order technique (RKFT45) with shooting-scheme and analytically via Duan–Rach Approach (DRA). It is found that the nondimensional temperature θ (η) is a decreasing function of a wet porous number m2 and convective parameter Nc for both insulated and convective tips, and as an increasing function of ambient temperature θa, Peclet number Pe and power index n. It is also found that the thermal profile θ (η) presents a decrease for all considered shape factors in the cases of insulated and convective tips boundary conditions. Computational results and those obtainable in the previous works have been used to verify and strengthen the results gained by the analytical DRA technique.
FDA*: A FOCUSED SINGLE‐QUERY GRID BASED PATH PLANNING ALGORITHM
(Journal of Automation, Mobile Robotics and Intelligent Systems, 2022-02-09) Boumediene Mouad; Mehennaoui Lamine; Lachouri Abderazzak
Square grid representations of the state‐space are a com‐ monly used tool in path planning. With applications in a variety of disciplines, including robotics, computatio‐ nal biology, game development, and beyond. However, in large‐scale and/or high dimensional environments the creation and manipulation of such structures become too expensive, especially in applications when an accurate re‐ presentation is needed. In this paper, we present a method for reducing the cost of single‐query grid‐based path planning, by focu‐ sing the search to a smaller subset, that contains the optimal solution. This subset is represented by a hyper‐ rectangle, the location, and dimensions of which are cal‐ culated departing from an initial feasible path found by a fast search using the RRT* algorithm. We also present an implementation of this focused discretization method cal‐ led FDA*, a resolution optimal algorithm, where the A* algorithm is employed in searching the resulting graph for an optimal solution. We also demonstrate through si‐ mulation results, that the FDA* algorithm uses less me‐ mory and has a shorter run‐time compared to the classic A* and thus other graph‐based planning algorithms, and at the same time, the resulting path cost is less than that of regular RRT based algorithms.
Stabilization of the cart-inverted-pendulum system using trivial state-feedback to output-feedback control conversion
(Automatika, 2022-04-15) Messikh Lotfi; Guechi El-Hadi; Bourahala Fayçal; Sašo Blažič
A new linear observer-free output-feedback controller with five adjustable parameters is proposed to stabilize the cart-inverted-pendulum system (CIP) at the unstable equilibrium point. The controller architecture is deduced from a trivial conversion of the linear state-feedback controller that is obtained using a two-step method. First, based on a set of cart change variables, a slightly modified state-feedback controller is developed. Then, the output-feedback controller is obtained through the judicious combination of the cart step reference input internal model and a convenient open-loop state estimator with the above modified state-feedback controller. The local stability of the output-based control system is conducted using the signature formulas method to get simplified conditions. A partial single parameter tuning method and optimal global single parameter tuning method are proposed for adjusting the controller gains to maximize a new efficiency-based objective function. Numerical simulations are first conducted to reveal the simplicity of output-feedback controller design using the partial tuning method, where the state-feedback gains are assumed to be known. Then, an optimal output-feedback controller is designed using the global tuning method. The proposed output-feedback controller is equivalent in terms of performance efficiency to the best five-parameter output-feedback two PID controller.
In Search of Preferential Macrocyclic Hosts for Sulfur Mustard Sensing and Recognition: A Computational Investigation through the New Composite Method r2SCAN-3c of the Key Factors Influencing the Host-Guest Interactions
(journal Nanomaterials, 2022-07-22) Fatine Ali Messiad; Ammouchi Nesrine; Youghourta Belhocine; Hanan Alhussain
Sulfur mustard (SM) is a harmful warfare agent that poses a serious threat to human health and the environment. Thus, the design of porous materials capable of sensing and/or capturing SM is of utmost importance. In this paper, the interactions of SM and its derivatives with ethylpillar[5]arene (EtP[5]) and the interactions between SM and a variety of host macrocycles were investigated through molecular docking calculations and non-covalent interaction (NCI) analysis. The electronic quantum parameters were computed to assess the chemical sensing properties of the studied hosts toward SM. It was found that dispersion interactions contributed significantly to the overall complexation energy, leading to the stabilization of the investigated systems. DFT energy computations showed that SM was more efficiently complexed with DCMP[5] than the other hosts studied here. Furthermore, the studied macrocyclic containers could be used as host-based chemical sensors or receptors for SM. These findings could motivate experimenters to design efficient sensing and capturing materials for the detection of SM and its derivatives.
Faults Diagnosis in PV Systems Using Structured Residuals and Indicator Parameters Techniques
(Journal Européen des Systèmes Automatisés, 2023-04-05) Boukoffa Kamel; Metatla Abderrezak; Louahem Msabah Ilyes; Benzahioul Samia
The detection and identification of some types of faults in PV systems is often difficult, because it is not possible to distinguish the noise coming from external factors and the influence of some faults on the parameters generated by PV systems. Until today, scientific works have focused more on the detection and identification of faults affecting a PV system. These works are focused on the application of different sophisticated and unsophisticated techniques. Therefore, the possibility of obtaining significant information about faults requires the development of more advanced techniques. The presented work consists of studying the influence of defects on the behavior of a photovoltaic system. In the first part, the work aims to present a signal processing technique based on the analysis of structured residual. In the first step of this part, the generated currents by the GPV are presented with the three operating modes: healthy, shading fault and progressive resistance fault, in the second step, the prediction errors of the current vectors from the three operating scenarios of the GPV are calculated. The evaluation of the developed approach, shows the efficiency and the identification precision of this method. In the second part, a technique based on the SEA method (Shape exchange algorithm) is presented whose diagnostic indicators were calculated, these indicators were classified according to their degree of criticality into three main categories. The obtained results show the effectiveness of this technique and the possibility of further increasing the detection and identification performance of faults in the PV system.
Tolerance Synthesis of Delta-like Parallel Robots Using a Nonlinear Optimisation Method
(Applied Sciences, 2023-07-26) Allaoua Brahmia; Adlen Kerboua; Ridha Kelaiaia; Ameur Latreche
Robotic systems require high accuracy in manipulating objects. Positioning errors are influenced by geometric tolerances and various sources. This paper introduces a new technique based on the interior-point algorithm optimisation method to allocate tolerances to the geometric parameters of a robot. This method consists of three steps. First, a method for modelling the kinematic problem as well as the geometric errors must be used. The Denavit–Hartenberg rule is the most suitable method for this modelling case. Then, a mathematical model for tolerance allocation is developed and used as a nonlinear multivariable optimisation problem. Finally, the “interior-point” algorithm is used to solve this optimisation problem. The accuracy and efficiency of the proposed method, in determining the tolerance allocations for a Delta parallel robot, is illustrated via calculation and simulation results. The values of the dimensional tolerances found are optimal. As a result, these values always keep the accuracy less than or equal to the imposed value.
Multi-objective Optimal Power Flow and Emission Index Based Firefly Algorithm
(Periodica Polytechnica Electrical Engineering and Computer Science, 2023-10-21) Nabil Mezhoud
The economic operation of electric energy generating systems is one of predominant problems in energy systems. In this work one evolutionary optimization method, based on the meta-inference behavior called the Firefly Algorithm (FFA) is applied to solve such as the multipurpose optimum power flow (OPF) and emission index (EI) problems. Our main goal is to improve the objective function necessary to achieve the best balance between production and its energy consumption, which is presented as a non-linear function, taking into account some constraints of equality and inequality. The goal is to reduce the total cost of generations, active losses, and emission index. The FFA approach was examined and tested on a standard IEEE-30 bus system. The validations of obtained results were compared with some well-known and recently published references. The efficiency and credibility of the proposed method has been proven by the obtained results.
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.
The Objective Oriented Design of a CUBE Cable - based Parallel Robot for Arm Rehabilitation Tasks
(WSEAS TRANSACTIONS on SYSTEMS, 2023-10-31) FOUED INEL; MOHAMMED KHADEM; ABDELGHAFOUR SLIMANE TICH TICH
- Rehabilitation robots have been employed for training of neural impaired subjects or for assistance of those with weak limbs. A cube, cable-based parallel robot with eight cables designed for assisting patients in upper-limb rehabilitation activities, with control over the end-location effector's while locking its rotation around the horizontal and vertical axes, the device has a lightweight structure that is simple to set up and use for home usage for both pre-determined and personalized exercises. In this context, we have limited the tensions of the cables (always positive) and the lengths of the robot do not exceed the workspace. In addition, the design's kinematic and dynamic studies are presented. The aim of this paper is to help the patient rehabilitate the upper limb in axes (y-z) and (x-y) with improved patient safety, such that the arm for the patient can move it in the two planes. The simulation exercises with solidworks and matlab software demonstrate the effectiveness of our proposed design
Improvement of Productivity in Buildings Construction
(SSP - JOURNAL OF CIVIL ENGINEERING, 2023-12) Chemseddine Dehchar; Khaled Boudjellal; Mohamed Bouabaz
Improving productivity in construction projects has long been a major concern, and much research has been carried out to try to ameliorate construction productivity. To this end, this study aims to improve and increase the productivity rate of flat slab formwork used in residential construction projects. A survey consisting of 150 questionnaires was undertaken to identify the factors that influence on the productivity. Based on the relative Importance Index (RII), data on eleven factors deemed to affect productivity were selected. A collection of 100 data points from various sites were utilized to develop two models. Firstly, an Artificial Neural Network (ANN) model was employed, and secondly, a parametric approach was investigated. The data were divided into two sets, with 70% of the data used for training and the remaining 30% used for testing. The models' performance was evaluated using the Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) values. In the test phase, the artificial neural network model yielded an MSE value of 2.6610e-4 and a MAPE value of 4.9227, whereas the parametric model produced an MSE of 0.040 and a MAPE of 9.525. It was found that the artificial neural network model provided reliable prediction accuracy compared to the parametric model. However, the artificial neural network approach can be selected as a robust model in predicting and controlling the productivity rate in local construction projects by using the developed model based on the identified factors.
Wind Driven Optimization based Optimal Energy Management of Microgrid Impregnated with Renewable Energy Sources
(Algerian Journal of Renewable Energy and Sustainable Development, 2023-12-05) Nabil Mezhoud; Ahmed Bahri; Bilel Ayachi
The desire for increased dependability, high energy quality, reduced cost, and a clean environment has led to a rise in the use of renewable energy sources (RES) in recent years, such as solar energy and wind energy. In this study, the optimal energy management (OEM) problem of a microgrid (MG) infused with RES is solved through the application of a nature-inspired meta-heuristic approach termed Wind Driven Optimisation (WDO), which is based on atmospheric motion. Our primary purpose is to minimise the nonlinear objective function of an electrical microgrid, which is expressed by minimising the MG operating cost while accounting for various operational limits related to equality and inequality through the best possible OEM control variable adjustment. A variety of DGs, including fuel cells (FC), wind turbines (WT), photovoltaic systems (PV), micro turbines (MT), and loads with energy storage systems (ESS), have been studied and tested using the WDO approach on MG linked. The outcomes show how the suggested strategy may effectively and robustly tackle OEM problems in various operational circumstances, which is encouraging. The suggested method's outcomes were verified and compared to those of reputable references that were recently published.
Green and Fast Extraction of Chitin from Waste Shrimp Shells: Characterization and Application in the Removal of Congo Red Dye
(Separations, 2023-12-13) Fatma Zohra Gharbi; Nabil Bougdah; Youghourta Belhocine; Najoua Sbei
Due to their detrimental and carcinogenic effects, synthetic organic dyes pose significant environmental and health risks. Consequently, addressing the bioremediation of industrial wastewater containing these organic dyes has become an urgent environmental concern. The adsorption using low-cost and green materials is one of the best alternative techniques for the removal of dyes. This study aims to investigate the use of chitin to eliminate Congo red (CR), an anionic dye, from wastewater. The chitin was produced from shrimp shell in a quick and environmentally friendly manner by utilizing a co-solvent (glycerol/citric acid (GLC)). The resulting adsorbent was characterized through various techniques, including X-ray diffraction (XRD), scanning electron microscopy (SEM), and FT-IR spectroscopy. The effectiveness of CR removal with chitin was studied with respect to contact time, adsorbent dose, initial pH, equilibrium isotherms, and kinetic and thermodynamic parameters. It was observed that variations in the dye concentration and pH significantly influenced the removal of CR with chitin. Under optimal operating conditions (pH = 7, contact time = 130 min, temperature = 50 ◦C), the adsorption capacity reached 29.69 ± 0.2 mg/g. The experimental data revealed that CR adsorption onto a chitin adsorbent is better represented by a Langmuir isotherm.
Weibull Statistic and Artificial Neural Network Analysis of the Mechanical Performances of Fibers from the Flower Agave Plant for Eco-Friendly Green Composites
(JOURNAL OF NATURAL FIBERS, 2024-01) Lalaymia Imen; Belaadi Ahmed; Boumaaza Messaouda; Alshahrani Hassan
The research conducted focused on examining the unique properties of Agave Americana Flower Stem fiber (AAFS), particularly its behavior under quasi-static tensile conditions. A total of 200 AAFS fibers were subjected to tensile tests using a standard gauge length of 40 mm. Tests spanned seven groups with quantities (N) ranging from 30 to 200. The study aimed to understand the fibers’ mechanical traits, as tensile resistance and modulus of elasticity, and to see how different test quantities influence these properties. A significant observation was the dispersion of the tensile characteristics of AAFS fibers, a common trait of natural fibers. To understand this, we applied rigorous statistical tools, including the Weibull distribution at a 95% confidence interval and one-way ANOVA. A mathematical model was produced utilizing data from experiments regarding the tensile behavior of AAFS fibers. The ANN provided correlation coefficients (R2 ) of 0.9897, 0.9971, 0.9993, and 0.9939 for training, validation, testing, and all datasets respectively, which were able to accurately predict the experimental data. The proposed model would be of tremendous assistance to engineers and designers in obtaining green composite materials that are based on natural fibers and thereby more durable. These methods illuminated the patterns in our results, enriching our understanding of AAFS fiber mechanics

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