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    Maximizing enhanced oil recovery via oxidative cracking of crude oil: employing air injection and H2O2 with response surface methodology optimization
    (IOP publishing, 2024) Nouari, Omar; Hammadou née Mesdour, Souad; Boudjemaa, Hamada
    The utilization of air injection as a method to enhance oil recovery in oil fields has gained prominence due to its cost-effectiveness and widespread availability, particularly in heavy oil production. This study focuses on optimizing the oxidative cracking process of Algerian crude oil by employing air injection supplemented with H2O2 and analyzing the interaction of key operating parameters like temperature and catalyst amount using response surface methodology. The predicted values derived from the response functions closely aligned with experimental data, demonstrating high accuracy (R2= 0.9727 for liquid oil, R2= 0.9176 for residue, and R2= 0.7399 for gas phases). Using the developed second-order model, optimal conditions were determined through contour and surface plots, as well as regression equation analysis using Design software. At these optimal parameters (14.78 wt% of H2O2, 2 l min−1 of air flow, 100 ml of crude oil at 354.05 °C for 40 min), the oxidative cracking process yielded 96.32% liquid oil, 3.018% residue, and 0.662% gas products. Notably, the experimental produced liquid oil constituted 96.07 vol. %, matching well with the optimization outcomes. Physicochemical analysis of liquid product phase obtained from oxidative cracking process of petroleum confirmed the prevalence of light aliphatic compounds(C2-C11) at 70.59%, alongside 29.41% of C12-C36. The process also resulted in reduced viscosity, density, refractive index, and sulfur content in the liquid phase. The combination of air injection and H2O2 showcases promise in recovering residual oil effectively and contributes to the ongoing advancements in EOR techniques.
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    Statistical optimization of microwave-assisted extraction of phytochemicals from Retama raetam (white weeping broom) twigs and their biological properties
    (AfAc Publisher, 2024) Zaoui, Oussama; Oughlissi-Dehak, Karima; Bouziane, Mebarka
    ackground: Several phytochemicals derived from the genus Retama reported to possess diverse biological activities, including antioxidant, anti-inflammatory, and antibacterial properties. Aims: The aim of this study was to optimize microwave-assisted extraction (MAE) of polyphenols from Retamaraetam twigs using response surface methodology. Methods: A Box-Behnken design was utilized for determining the effect of MAE factors on total polyphenol content (TPC), including ethanol concentration (50 – 70%), irradiation time (4 – 6 min), power (400 – 600 W), and solvent-to-sample ratio (15 – 25 mL/g). The optimal extract (OE) was further analyzed for total flavonoid content (TFC), total tannin content (TTC), and antioxidant activity (DPPH• scavenging and FRAP) andin vitro anti-inflammatory activity assessment of the OE was evaluated using two complementary assays (albumin denaturation and membrane stabilization). Results: The following conditions: ethanol concentration of 64.73%, irradiation time of 5.57 min, power of 569.16 W, and solvent-to -sample ratio of 22.91 mL/g, resulted in the highest TPC (181.48 ± 1. 59 mg GAE/g DR). The effectiveness and statistical validity of the derived quadratic model indicated no significant discrepancies between experimental and predicted results, demonstrating its high degree of accuracy. The obtained OE demonstrated a TFC of 31.25 ± 1.5 mg EC/g DR and a TTC of 15.17 ± 1.56 mg EC/g DR. The OE showed a significant capacity to scavenge DPPH• and an appreciable ferric-reducing power, where the IC50 and EC50 values were respectively 0.44 ± 0.08 and 0.61 ± 0.03 mg/mL. At a concentration of 1.5 mg/mL, the OE displayed moderate anti-inflammatory activity by red blood cell membrane stabilization (72.72 ± 0.73%) and reduction of heat-induced albumin denaturation (50.89 ± 0.66%). Conclusion: The MAE of TPC from Retama raetam twigs was primarily influenced by EtOH concentration, irradiation time, and power. The OE exhibited moderate antioxidant and anti-inflammatory properties, suggesting its potential as a source of phytopharmaceuticals.
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    Removal of Amoxicillin From Wastewater Onto Activated Carbon: Optimization of Analytical Parameters by Response Surface Methodology
    (SAGE Publications Inc., 2024) Abbas, Moussa; Trari, Mohamed
    Antibiotics are widely used in veterinary and human medicine, but these compounds, when released into the aquatic environment, present potential risks to living organisms. In the present study, the activated carbon (AC) used for their removals is characterized by FT-IR spectroscopy, BET analysis and Scanning Electron Microscopy (SEM) to determine the physicochemical characteristics. Response surface methodology (RSM) and Box-Behnken statistical design (BBD) were used to optimize important parameters including pH (2-12), temperature (20-45°C), and AC dose (0.05-0.20 g). The experimental data were analyzed by analysis of variance (ANOVA) and fitted to second-order polynomial using multiple regression analysis. The optimal conditions for maximum elimination of Amoxicillin (Amox) are (Dose: 0.124 g, pH 5.03 and 45°C) by applying the desirability function (df). A confirmation experiment was carried out to evaluate the accuracy of the optimization model and maximum removal efficiency (R = 89.999%) was obtained under the optimized conditions. Several error analysis equations were used to measure goodness of fit. Pareto analysis suggests the importance of the relative order of factors: pH > Temperature > AC dose in optimized situations. The equilibrium adsorption data of Amox on Activated Carbone were analyzed by Freundlich, Elovich, Temkin and Langmuir models. The latter gave the best correlation with qmax capacities of 142.85 mg/g (R2 = 0.999) at 25°C is removed from solution. The adsorption process is dominated by chemisorption and the kinetic model obeys a pseudo-second order model (R2 = 0.999).
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    A Taguchi method-based optimization algorithm for the analysis of the wind driven-self-excited induction generator
    (Institute of Advanced Engineering and Science (IAES), 2024) Boukenoui, Rachid; Bradai, Rafik; Kheldoun, Aissa
    This paper investigates the use of a new global optimization algorithm that is based on Taguchi method to determine the performance parameters of self-excited induction generator being driven by variable speed wind. This analysis is based on solving equations obtained from the per-phase equivalent circuit of the induction generator. The equations have two unknowns namely the frequency and the magnetizing reactance. Both unknown are strongly dependent on the wind turbine speed, the capacity of the excitation, the load being connected at the terminals of the stator and eventually the per-phase equivalent circuit parameters. The resulting equations are nonlinear and subsequently to solve them one can employ either gradient-based algorithms or heuristic algorithms. This paper uses a new heuristic algorithm based on the Taguchi method which, in addition to its global research capability, offers superior characteristics in terms of accuracy and ease of implementation. A comparison with recently published optimization methods is carried out to show its performances in terms of accuracy and ease of implementation. The MATLAB software will be used to perform this analysis on a machine of 0.75 kW while some will be validated experimentally to confirm the aforementioned benefits.
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    Wind Turbine Mechanical Speed Regulation Reliability Of Artificial Intelligent PSO-FLC Control
    (Institute of Electrical and Electronics Engineers Inc, 2024) Arabi, Marwa; Zennir, Youcef; Bourourou, Fares
    this paper addresses modeling and control of a wind energy conversion system (WECS). The WECS based on Permanent Magnet Synchronous Generator, PMSG. Wind energy transformed to mechanical energy via blade and turbine to give speed and torque to the PMSG. This mechanical speed will be controlled firstly with a classical MPPT-PI then will be optimized by a PSO algorithm, after that a new intelligent controller MPPT-FLC will be applied to show the efficiency of that's kind of controller on our WECS mechanical speed control. The analysis and discussion of the simulation results aim to enhance the reliability and efficiency of each suggested approach. Keywords - Wind turbine, Speed control, Optimization, FLC, PSO, PI.
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    A New Fast and Efficient MPPT Algorithm for Partially Shaded PV Systems Using a Hyperbolic Slime Mould Algorithm
    (Wiley-Hindawi, 2024) Belmadani, Hamza; Bradai, Rafik; Kheldoun, Aissa; Mohammed, Karam Khairullah; Mekhilef, Saad; Belkhier, Youcef; Oubelaid, Adel
    The design of new efficient maximum power point tracking (MPPT) techniques has become extremely important due to the rapid expansion of photovoltaic (PV) systems. Because under shading conditions the characteristics of PV devices become multimodal having several power peaks, traditional MPPT techniques provide crappy performance. In turn, metaheuristic algorithms have become massively employed as a typical substitute in maximum power point tracking. In this work, a new optimizer, which was named the hyperbolic slime mould algorithm (HSMA), is designed to be employed as an efficient MPPT algorithm. The hyperbolic tangent function is incorporated into the optimizer framework equations to scale down large perturbations in the tracking stage and boost its convergence trend. Moreover, to provide a strong exploration capability, a new mechanism has been developed in such a way the search process is carried out inside the best two power peak regions along the initial iterations. This region inspection mechanism is the prime hallmark of the designed optimizer in avoiding local power peaks and excessive global search operations. The developed algorithm was examined through diverse complicated partial shading conditions to challenge its global and local search abilities. A comparative analysis was carried out against the well-regarded PSO, GWO, and the standard slime mould algorithm. In overall, the designed optimizer defeated its contenders in all aspects offering higher efficiency, superior robustness, faster convergence, and fewer fluctuations to the operating point. An experimental setup that consists of the DSpace microcontroller and a PV emulator was employed to validate the algorithm overall performance. The recorded outcomes outline that the developed optimizer can achieve a tracking time of 0.6 seconds and 0.86 seconds on average, with 99.85% average efficiency under complex partial shading conditions.
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    DEMAP: differential evolution mapping for network on chip optimization
    (Intelektual Pustaka Media Utama, 2023) Bougherara, Maamar; Amara, Rafik; Kemcha, Rebiha
    Network-on-chip (NoC) is a new paradigm for system-on-chip (SoC) design, which facilitates the interconnection and integration of complex components. Since this technology is still new, significant research efforts are needed to ac-celerate and simplify the design phases. Mapping is a critical phase in the NoC design process, as a mismatch of application software components can signif-icantly impact the final system’s performance. Therefore, it is essential to develop automated tools and methods to ensure this step. The main objective of this project is to develop a new approach that can be used to map applications on the NoC architecture to reduce communication costs. To achieve this goal, we have opted for an optimization algorithm, specifically the differential evolution algorithm.
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    Improvement of system reliability in a natural gas processing facility by PSO and DE
    (Springer Nature, 2024) Saheb, Tafsouthe; Mellal, Mohamed Arezki
    The reliability of the systems as well as its optimization is the first concern of the designers. The elements of a given system can be either in series, parallel, parallel-series, or in a complex configuration. This paper addresses the reliability optimization of a natural gas processing facility. The reliability of this system is calculated and two redundancies strategies, active and standby, are optimized under the resource limits to improve reliability. Two bio-inspired optimization algorithms, namely the particle swarm optimization (PSO) and the differential evolution (DE), are implemented with penalty functions to find the optimal redundancy. The results obtained are compared.
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    A novel hybrid Chaotic Aquila Optimization algorithm with Simulated Annealing for Unmanned Aerial Vehicles path planning
    (Elsevier, 2022) Ait Saadi, Amylia; Meraihi, Yassine; Soukane, Assia; Benmessaoud Gabis, Asma; Amar Ramdane, Cherif
    In recent years, research on Unmanned Aerial Vehicles (UAVs) has become one of the interest- ing topics for industry and academic. UAV path plan- ning is one of the critical issues in terms of guaran- teeing the autonomy and good performance of UAVs in real-world applications. Its main objective is to de- termine and ensure an optimal and collision-free path between two positions from a starting point (source) to a destination one (target) while satisfying some UAV requirements (i.e. UAV’s safety, environment complex- ity, obstacle avoidance, energy consumption,etc). Due to the complexity of this topic, an efficient path plan- ning algorithm is required. This paper presents an opti- mal and hybrid algorithm, called CAOSA, based on the hybridization of Chaotic Aquila Optimization (CAO) and Simulated Annealing (SA) algorithms for solving the UAV path planning problem in a 3D environment. As a first step, chaotic map is introduced to enhance the chaotic stochastic behavior of the Aquila Optimization (AO) algorithm. In the second step, the SA algorithm is combined with CAO algorithm to improve the best so- lution (path quality) obtained after each iteration of COA. The main purpose of using SA is to increase the exploitation by searching for the most promising regions identified by the CAO algorithm. The perfor- mance of the proposed CAOSA algorithm is evaluated on several scenarios under different settings consider- ing the fitness value, path cost, and execution time metrics. Simulation results showed superiority and ro- bustness of CAOSA algorithm compared to nine meta- heuristics such as Simulated Annealing (SA), Particle Swarm Optimization (PSO), Bat Algorithm (BA), Fire- fly optimization (FA), Grey Wolf Optimizer (GWO), Sine Cosine Algorithm (SCA), Whale Optimization Al- gorithm (WOA), Dragonfly Algorithm (DA), and the original Aquila Optimization (AO). It is also revealed that CAOSA can offer an optimized path that improves UAV path planning requirements significantly in com- plex environments
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    Optimization of partially hydrolyzed polyacrylamide (HPAM) utilized in water-based mud while drilling
    (MDPI, 2023) Sid, Asma Nour El Houda; Kouini, Benalia; Bezzekhami, Mohammed Amin; Toumi, Selma; Ouchak, Khadidja; Benfarhat, Sara; Tahraoui, Hichem; Kebir, Mohammed; Amrane, Abdeltif; Assadi, Aymen Amine; Zhang, Jie; Mouni, Lotfi
    Water-soluble polymers are becoming increasingly important in various applications, such as stabilizer fluids and drilling muds. These materials are used as viscosifiers and filtration control agents, flocculants, and deflocculants due to their superior properties in increasing viscosity and gelling ability in the presence of crosslinkers. In general, studying the rheological behavior of drilling fluids is of paramount importance to ensure successful well drilling operations. Partially hydrolyzed polyacrylamide is one of the polymers widely used in water-based muds. The main objective of this study is to optimize the rheological properties of drilling muds through a characterization study of various parameters, including rheological behavior, viscosity, temperature (23 °C, 40 °C, and 60 °C), salinity using KCl and NaCl contents, aging, pH, solubility, and structural analysis using infrared of partially hydrolyzed polyacrylamide. The study aims to demonstrate the importance of using polymers in drilling muds. The findings revealed that a rate of 3% of HPAM gave better rheological behavior, the influence of KCl (1.5%, 3%, and 4.5%) was greater than that of NaCl (1.5%, 3%, and 4.5%) on polymers, and the aging test showed that the different formulations are stable and maintain their behavior up to 110 °C. The solubility test results confirmed the maximum amount absorbed by polyacrylamide ([CHPAM] = 66.42 g/L) in order to avoid aggregation, gelification, and enhance the drilling mud by utilizing the prescribed contents