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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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    Data aggregation point placement optimization in Smart Metering Networks
    (JES, 2024) Grainat, Youcef; Recioui, Abdelmadjid; Oubelaid, Adel
    This study explores the application of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) within the framework of smart grids (SG), specifically for the optimal placement of data aggregation points (DAPs) across a network of 150 Z-wave smart meters distributed within various smart cities. The investigation aims to identify which of the two- optimization strategies offers a more cost-efficient solution while evaluating their performance in terms of transmission average latency (AL) and execution time (ET) efficiency. The results indicate that although ACO slightly edges out PSO in reducing overall costs in networks with a higher complexity and more DAPs, PSO demonstrates superior performance in execution speed, lower AL, and total cost, underscoring its viability for swift integration in smart metering infrastructures.
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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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    Data Caching in Edge Computing: A Survey
    (Institute of Electrical and Electronics Engineers Inc., 2024) Kara, Meliha Çağla; Benlakehal, Mohamed Elamine; Shayea, Ibraheem; Tussupov, Akhmet; Rzayeva, Leila
    As the Internet of Things (IoT) generates ever-increasing data streams, traditional cloud-centric architectures face crippling challenges in network latency, bandwidth consumption, and resource constraints. This paper explores how data caching in edge computing environments emerges as a potent solution, significantly impacting latency reduction, network efficiency, and overall system performance. We comprehensively review the landscape of edge IoT and data caching, analyze caching benefits and complexities, and delve into architectural integration, caching strategies, and algorithms tailored to address specific IoT challenges. Through case studies in chosen application domains, we quantify the performance improvements enabled by effective caching and pave the way for future research exploring novel caching methodologies and optimization techniques in the dynamic world of edge IoT.
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    Wireless Power Transfer Optimization Using Meta-heuristic Algorithms
    (IEEE, 2024) Bennia, Fatima; Boudouda, Aimad; Nafa, Fares
    The importance of Wireless Power Transfer (WPT) technology in biomedical implants to mitigate the risk of regeneration has increased significantly in recent years. WPT systems are dependent on key parameters such as the coupling coefficient (K), quality factor (Q), and mutual inductance (M), which play a crucial role in determining power transfer efficiency. These parameters are closely related to the geometric characteristics of the coils involved. Therefore, this study explores various meta-heuristic algorithms to search for optimal parameters that maximize power transfer efficiency. The initial results demonstrate that these algorithms perform well across different iterations. To confirm these findings, the study conducted comprehensive validation using Ansys Maxwell software to verify the optimal values obtained through optimization.
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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.