STUDIES IN ENGINEERING AND EXACT SCIENCES <p>The <strong>STUDIES IN ENGINEERING AND EXACT SCIENCES (SEES)</strong> publish an academic-scientific article on topics related to the areas of Engineering and Exact Sciences, plus the subfields, Civil Engineering, Mining Engineering, Materials and Metallurgical Engineering, Electrical Engineering, Mechanical Engineering, Chemical Engineering, Sanitary Engineering, Production Engineering, Nuclear Engineering, Transportation Engineering, Marine and Ocean Engineering, Aerospace Engineering, Biomedical Engineering, Mathematics, Probability and Statistics, Computer Science, Astronomy, Physics, Chemistry.</p> <p style="margin: 0cm; margin-bottom: .0001pt; text-align: justify; background: white;">The SEES accepts contributions written in <strong style="box-sizing: border-box;">Portuguese</strong>, <strong style="box-sizing: border-box;">English</strong> or <strong style="box-sizing: border-box;">Spanish</strong>.</p> <p>DOI prefix of SEES: <strong>10.54021</strong></p> <p style="text-align: justify;">ISSN: <strong>2764-0981</strong></p> <p style="text-align: justify;">Area of ​​knowledge: <strong>Engineering and Exact Sciences, plus the subfields</strong></p> <p> </p> <p> </p> Profa. Barbara Bonfim, MSc. en-US STUDIES IN ENGINEERING AND EXACT SCIENCES 2764-0981 A new multi-function smart electricity measurement device <p>Algeria's national gas and power provider is called Sonelgaz. It is in charge of producing, distributing, and transmitting power throughout the nation. Sonelgaz has encountered several difficulties in effectively supplying electricity to consumers and keeping track of their usage over the years. One of the primary problems is that client consumption is not accurately metered. Algeria has a large number of old power meters that don't give precise readings of the real electrical usage. Customers receive inaccurate bills as a result of this. It also makes it more challenging for Sonelgaz to monitor usage trends and detect power thieves. Poor metering infrastructure has led to disputes between Sonelgaz and customers over excess bills. In recent years, the idea of a smart power meter has become increasingly popular all around the world. Traditionally, readings must be taken in the meter reading room. As a result, tracking and keeping tabs on your electricity usage is a time-consuming and annoying chore. Furthermore, a lot of us worry about our large electricity bills at the end of the month, therefore, we have to periodically check the energy meter. However, what if we could track how much electricity we consume from anywhere in the world? In this paper, we will develop a new multi-function smart electricity measurement device using an ESP32 microcontroller and the mobile Blynk app. The smart electricity measurement device displays the voltage, current, power factor, and power consumption in real time. In addition, it displays the cost of electricity in dollars and the total energy consumed in kWh, saving you both time and money. The consumer's electricity will be remotely off if the bills are not paid.</p> Saad Khadar Rabhi Nadjoua Missaoui Isra Oumaima Aggoun Hanane Aya Copyright (c) 2024 2024-07-02 2024-07-02 5 2 e5366 e5366 10.54021/seesv5n2-001 Enhanced energy storage system efficiency for remote area-based DC microgrid <p>This article suggests a hybrid storage system-based DC microgrid to supply the needs of remote areas with variable loads demands. This would help solve problems like limited energy storage systems, complicated consumption, and unstable power production from renewable sources. Energy storage is an attractive option for isolated zone; however, a single storage unit may not be sufficient owing to constraints in capacity, power, energy density, and life cycle. consequence, this study is concerned with hybrid energy storage systems battery/supercapacitor, which combine the most advantageous characteristics of various energy storage technologies to attain relevant performance. Furthermore, the supervision energy management technique based decoupling frequency is designed with low pass filter to separate the current to tow elements, low frequency current absorbed by the battery and high frequency current that absorbed by the supercapacitor. Furthermore, PI controllers are employed to control the DC link voltage, and the current of battery and supercapacitor. Energy management control plays an important role to improve the system performance, ensure power allocation among source, storage devices, and load consumption, and to maintain the battery and supercapacitor at their limitation states of charge (SOC), the system must be able to match the load requirements during a shortage and absorb any surplus power provided by wind energy. To confirm the achievement of the objectives of this study, the comparative simulation between battery storage alone and hybrid storage system combined of battery and Supercapacitor. The simulation results show that the hybrid storage battery and supercapacitor allow to increases the stability of DC link voltage with an overshoot less than 1.5% compared to 7.5% when battery alone and fast dynamic response. in addition, reduces the battery stress and increases its lifetime in the case of hybrid storage.</p> Mohammed Abdulelah Albasheri Ouahid Bouchhida Youcef Soufi Abdelhafidh Cherifi Copyright (c) 2024 2024-07-02 2024-07-02 5 2 e5367 e5367 10.54021/seesv5n2-002 Assessing the impact of discarded plastic bottles on the resistance to rutting in hot mix asphalt <p class="referencias" style="text-align: justify;">Undoubtedly, the damage to the upper layer of road pavement caused by the tremendous load of vehicles and climate factors is alarming and challenging to both the government and researchers in the respective field. Addressing these challenges requires innovative solutions to enhance pavement durability and sustainability. In this context, the authors seek to assess the impact of incorporating waste polyethylene terephthalate (PET) as a modifier on asphalt mixture properties. This study investigates the potential of PET, a commonly discarded plastic, to improve the performance of asphalt pavements. The authors conducted evaluations on the rutting performance of asphalt blends containing different PET percentages (0%, 0.2%, 0.6%, 0.8%, 1%) and diverse PET sizes (12 × 3 mm, 20 × 3 mm, and 30 × 4 mm). The experimental approach included dynamic creep tests and the use of a Hamburg wheel tracking device to simulate real-world traffic conditions and measure the mixtures' resistance to deformation. The findings revealed that incorporating PET into asphalt mixtures significantly enhances rutting resistance. Specifically, the addition of PET content improved the viscoelastic properties of the asphalt, making it more resistant to permanent deformation under load. However, the size of PET particles was found to play a crucial role in performance. Larger PET sizes were associated with a decrease in rutting resistance, suggesting an optimal particle size must be determined to maximize benefits. These results support the idea that the careful selection of PET content and size can significantly improve the performance and longevity of asphalt pavements. This approach not only addresses the issue of plastic waste but also contributes to the development of more sustainable infrastructure. By incorporating PET, the research highlights a viable method for enhancing road durability and supporting environmental sustainability, offering a promising solution for future road construction projects.</p> Mohamed Lakhder Guesmi Abdelhak Bordjiba Mohamed Guesmi Copyright (c) 2024 2024-07-02 2024-07-02 5 2 e5368 e5368 10.54021/seesv5n2-003 Deep-modified transfer learning-based CNN networks for enhanced breast cancer prediction <p>Breast cancer (BC) is one of the most fatal forms of cancer, making it a significant contributor to mortality rates worldwide. Early detection and timely treatment of breast cancer are crucial in reducing its mortality rate. To ensure a healthy lifestyle, it is essential to develop systems that can accurately diagnose breast cancer. Recent advances in modern computing and information technologies have enabled significant progress in the early detection and prediction of diseases within healthcare systems. This study proposes a method for precise and automatic breast cancer prediction using deep-modified transfer learning-based Convolutional Neural Networks (CNNs). The CNN architectures employed include ResNet50, MobileNetV2, DenseNet121, and Xception, which serve as feature extractors to capture the most relevant features of breast Ultrasound images (BUSI). These extracted features are then accurately classified as benign or malignant using various high-performance classifiers, including Support Vector Machine (SVM), K-Nearest Neighbors (KNN), XGBoost, and Softmax. The experimental results demonstrate that the proposed deep modified DenseNet121 network with the Softmax classifier outperformed other models and existing techniques. This latter achieved remarkable performance metrics, including an accuracy of 95.34%, a precision of 90.90%, and an F1 score of 93.02%. These results highlight the effectiveness of our approach in enhancing the accuracy of breast cancer prediction. The superior performance of the proposed method provides significant improvements in decision-making speed and reduces the time, effort, and laboratory resources required for healthcare services. Consequently, this method has the potential to significantly enhance early diagnosis and enable more tailored treatment plans, ultimately contributing to better patient outcomes and reducing the overall mortality rates associated with breast cancer.</p> Tawfiq Beghriche Mohamed Djerioui Youcef Brik Bilal Attallah Copyright (c) 2024 2024-07-02 2024-07-02 5 2 e5383 e5383 10.54021/seesv5n2-004 Effect of recycled concrete aggregate size on physical and mechanical properties of eco-friendly-self-compacting concrete <p>In recent years, the rapid increase in population and building demand across the world leads to significant deterioration or reduction of natural resources. Meanwhile the huge amounts of waste from the demolition of buildings and concrete structures in the landfill space become a serious ecological and environmental problem. The recovery of aggregates from recycled concrete for the formulation of new concrete would contribute to reducing the depletion of natural resources and therefore integrate into the context of sustainable development, because there are several socio-economic advantages. The objective of this possibility of using aggregates from recycled concrete mixes. We have established a comparison between the physical and mechanical behavior of SCC based on RCA (Recycled Sand: SR 0/3 and Recycled Gravel RG: 3/8 and 8/15) and that of SCC based on natural aggregates (NA) on fresh support and hardened state. Additionally, Non-Destructive Testing (NDT) methods were conducted in this research to obtain more information about the properties of the studied SCC. The results of the tests on fresh SCC meet the recommendations of the French Association of Civil Engineering (AFGC). The physical and mechanical behavior of SCC-RS is relatively weak compared to SCC-NA/RG. This is directly related to the high absorption capacity of the aggregates (depending on the size of the aggregates) and the poor quality of the mortar attached to the aggregates, which can create areas of weakness in the concrete structure. From the regression results, it was found that there is a direct correlation between the physical and mechanical properties of different concretes indicated by the higher values of R-squared (R2 = 0.92).</p> Noureddine Agha Abdelkadir Makani Ahmed Tafraoui Said Zaouai Copyright (c) 2024 2024-07-02 2024-07-02 5 2 e5384 e5384 10.54021/seesv5n2-005 Virtual synchronous generator control with parameters optimization based on new WaOA algorithm for grid-feeding inverters <p>The widespread integration of renewable energy sources (RESs) within traditional power systems causes a considerable impact, such as a decrease in total inertia, damping properties, and large frequency deviation. To tackle this issue, numerous research have been proposed to introduce the virtual synchronous generator (VSG) control strategy as an effective solution applied to power electronics inverters operating in grid-forming or grid-feeding control modes. However, the proper tunning of the inertia and damping parameters is considered as a significant challenge to ensure the system stability and reliability. In this paper, an efficient meta-heuristic Walrus Optimization Algorithm (WaOA) -based VSG control intended for grid-feeding inverters within a weak grid is proposed. The objective of this work is to offer a proper tuning of the VSG parameters, thereby improving the dynamic characteristics of the microgrid (MG) and guaranteeing a stable operation. In addition, it highlights the adopted optimization technique which is introduced on VSG control while ensuring minimum objective function value. Through offline simulations in MATLAB/Simulink, the superiority of the suggested WaOA method is first confirmed, in which it offers the lowest Integral Square Error (ISE) fitness function value of 0.026, compared to the Mountain Gazelle Optimizer (MGO) and Tunicate Swarm Algorithm (TSA) with 0.027 9 and 0.0281, respectively. Second, the performance of the WaOA-based VSG control is compared to the ones based on MGO and TSA techniques under active and reactive power variations. The obtained results demonstrate that the proposed VSG control ensures a better transient performance, especially in terms of under and overshoots.</p> Abdelhak Hadj Kaddour Ouahid Bouchhida Ahmed Bendib Copyright (c) 2024 2024-07-02 2024-07-02 5 2 e5391 e5391 10.54021/seesv5n2-006 Assessment of methane emissions from landfills in five major cities of Algeria: comparative analysis of calculation models and study on methane-to-electricity conversion <p>Landfills are commonly used for managing municipal solid waste and generating energy. However, accurate estimations of landfill gas, thorough analysis of its energy potential, and comprehensive economic assessments are essential for the successful implementation of a landfill project. The municipal solid waste (MSW) generation rate in Algerian cities is experiencing an exponential increase alongside the growth of urbanization and commercial activities. Various waste-to-energy technologies have been explored in the past, but anaerobic digestion stands out as the preferred option due to its eco-friendly nature and simple design. This article presents a study on the potential of generating electrical energy from methane produced in landfills in five major cities in Algeria. Using various models to assess methane quantities, the study highlights a rising trend in methane production over the years, with peaks expected between 2032 and 2047 depending on the regions. The findings suggest that methane can be harnessed as an economical energy source, providing a sustainable solution to meet the growing energy needs of these regions. Additionally, the article underscores the importance of effective landfill management to minimize environmental impacts and maximize the economic benefits of this renewable energy source. In conclusion, this study provides crucial insights to guide public policies and private initiatives aimed at promoting the capture and utilization of landfill methane as a solution to reduce greenhouse gas emissions and facilitate a transition to a greener economy in Algeria, also it will aid local authorities in incorporating considerations of the potential for energy recovery in the study regions, as well as in other areas of Algeria, into their long-term waste management plans.</p> Abdelli Islam Safia Toumi Meriem Abdelmalek Fatiha Addou Ahmed Copyright (c) 2024 2024-07-03 2024-07-03 5 2 e5407 e5407 10.54021/seesv5n2-007 On the qualitative study of solutions of a class of nonlinear abstract dynamic equations on time scales and applications <p>The theory of dynamic equations on time scale was introduced in [7, 8] whose main objective is to provide a unified approach to continuous and discrete analysis. The calculus on time scales and dynamic equations on time scales have applications in any field that requires simultaneous modeling of continuous and discrete processes, because they bridge the divide between continuous and discrete aspects of processes. Perturbation theory is a pertinent discipline for the applications of time scale dynamics which is a compilation of methods systematically used to evaluate the global behavior of solutions of dynamical systems with occurrence on non uniform domains. One of the analytic methods of the perturbation theory was referred to integral inequalities to quest some type of stability. In the last few years, the search on qualitative properties of dynamics was directed to the time scale integral inequalities using diverse techniques and some significant results were obtained. Some of the original references on this approach include [1,2,3,4,5,9,10,11,12,13,14,17,22,24]. In this work, we study the h-stability problems of some classes of dynamic equations as an extension of exponential stability. We derive some sufficient conditions that guarantee h-stability of perturbed dynamic equations using Grönwall- typ integral inequality approach and Lyapunov function approach. We prove under certain conditions on the linear and nonlinear perturbations that the resulting perturbed nonlinear abstract dynamic equation still acquired h stable, if the associated dynamic equation has already owned this property. Finally, an numerical example is introduced to illustrate the applicability of the main results.</p> Safa Bouaoud Bilel Neggal Khaled Boukerrioua Copyright (c) 2024 2024-07-03 2024-07-03 5 2 e5408 e5408 10.54021/seesv5n2-008 Mechanical instabilities of nano-composite plates using elasticity theories <p>This study examines the mechanical buckling behavior of a simply supported rectangular polymer plate reinforced with carbon nanotubes (CNTs) using an efficient first-order shear deformation theory (FSDT). The Hamiltonian principle derives the equilibrium equations of the nano-composite plate, while Navier solutions define the boundary conditions, creating a model to determine the critical buckling load (λ<sub>cr</sub>). Various volume fractions (V<sub>cnt</sub> = 0.11, 0.14, 0.17) and CNT distributions [uniform (UD) and functionally graded (FG-X, FG-O, FG-V)] are considered in this analysis. Model validation occurs through comparison with established scientific literature. Furthermore, the model applies to various parametric changes, such as variations in plate geometry, changes in matrix or reinforcement properties, carbon nanotube orientations, loading types (uniaxial/biaxial), and buckling modes.</p> Hafid Khetir Abdelmoutalib Benfrid Mohamed Bachir Bouiadjra Rabie Zouaoui Harrat Mohammed Chatbi Copyright (c) 2024 2024-07-03 2024-07-03 5 2 e5409 e5409 10.54021/seesv5n2-009 Strengthening the security of end-to-end communication in photonic networks <p class="referencias" style="text-align: justify;"><span style="letter-spacing: -.2pt;">The burgeoning Internet and Internet-of-Things (IoT) sectors necessitate robust cryptographic methods to ensure data security, integrity, and authentication over unsecured networks. Traditional public key cryptography, reliant on computationally hard problems, faces threats from quantum computing advancements. Quantum Key Distribution (QKD) presents a solution through the generation of unconditionally secure cryptographic keys using quantum mechanics. This paper explores the enhancement of QKD protocols to establish secure end-to-end communication in photonic networks. The proposed method involves a QKD system that generates two types of weak quantum signals: one with randomly varied intensity, polarization, or phase, and another with random frequency fluctuations. These signals are used to establish a shared key between a transmitter (Alice) and multiple receivers (Bobs) by measuring the quantum states. This dual signal approach enhances protection against Photon Number Splitting attacks and improves key length. Key Management Agents (KMAs) securely handle QKD-generated keys for data encryption before transmission, ensuring only intended recipients can decrypt the messages. The system leverages optical fiber or free-space optical links to transmit weak quantum signals and synchronization signals, facilitating key distribution even under existing network constraints. The proposed architecture allows for the secure exchange of cryptographic keys between Alice and multiple Bobs, ensuring private and authenticated communication over public channels. The approach mitigates potential eavesdropping by enabling the detection of any interception attempts through Quantum Bit Error Rate (QBER) estimation. This study underscores the promise of QKD as a foundational element of future communication systems, providing uncrackable quantum keys and paving the way for secure photonic networks. Incremental advancements in quantum devices, networking, and infrastructure are essential to fully realize QKD's potential for robust cryptographic security.</span></p> Sellami Ali Benlahcene Djaouida Copyright (c) 2024 2024-07-03 2024-07-03 5 2 e5437 e5437 10.54021/seesv5n2-010 Optimum design of an off-grid PV/WT/FC/battery based microgrid for sustainable and cost-effective energy optimization <p>This paper presents an optimized microgrid based on a PV/wind/battery/fuel cell hybrid power system with a battery and hydrogen tank storage system for an islanded residential load. This advanced system is optimized using Smell Agent Optimization (SAO) and Genetic Algorithm (GA). The system is meticulously designed to meet the energy demand while minimizing the total annual cost. Simulation findings revealed that both SAO and GA yield comparable outcomes, as both effectively optimized the system, ensuring sustainability and efficiency in system sizing. Also, the optimized results obtained from SAO appear to be more effective in enhancing the overall performance of hybrid energy systems. The study demonstrates that the application of these algorithms not only optimizes the design but also contributes significantly to the reliability and economic feasibility of the microgrid. The dual storage approach, incorporating both battery and hydrogen tank, proves to be a robust solution for maintaining continuous power supply under diverse weather conditions. The findings suggest that the proposed system configuration and optimization methodology can serve as a benchmark for future studies in the field of renewable energy systems.</p> Manal Drici Mourad Houabes Ahmed Tijani Salawudeen Mebarek Bahri Copyright (c) 2024 2024-07-03 2024-07-03 5 2 e5438 e5438 10.54021/seesv5n2-011 As plataformas digitais educacionais e a Ciência de Dados <p class="referencias" style="text-align: justify;">Nos últimos anos, as plataformas digitais têm desempenhado um papel cada vez mais crucial no cenário educacional, transformando a maneira como o conhecimento é acessado, compartilhado e aplicado. Paralelamente, o advento da Ciência de Dados trouxe consigo novas perspectivas para a análise e interpretação de dados educacionais, oferecendo informações para melhorar tanto os processos de ensino quanto de aprendizagem. Diante desse contexto, o presente estudo se propôs a realizar uma revisão da literatura, com o objetivo de elucidar o estado atual das plataformas digitais educacionais e explorar como a Ciência de Dados tem sido empregada nesse contexto. Foram identificados 10 artigos pertinentes ao tema e considerados para a revisão. A revisão dos estudos sobre as plataformas digitais educacionais e Ciência de Dados revela que o <em>Google Meet</em> e <em>Google Classroom</em> são amplamente utilizadas para facilitar o ensino remoto, promovendo interação e distribuição de conteúdo. No entanto, a eficácia educacional não é garantida apenas pelo uso dessas ferramentas, requerendo alinhamento com objetivos específicos e superação de desafios como acesso limitado à internet. A análise dos artigos mostrou que as plataformas digitais variam no uso para ensino remoto, promovendo interação, distribuição de conteúdo e atividades em tempo real. No entanto, a eficácia do ensino depende de alinhar essas ferramentas aos objetivos educacionais e superar desafios como acesso à internet e problemas técnicos. A Ciência de Dados se destacou como aliada na análise dos dados dessas plataformas, ajudando a entender o desempenho dos alunos, padrões de aprendizagem e a eficácia dos métodos pedagógicos, além de apoiar a personalização da educação e o desenvolvimento de políticas educacionais baseadas em evidências. Essa combinação promete transformar o ensino globalmente, ampliando oportunidades e impulsionando a pesquisa educacional.</p> Ricardo Yukio Uratsuka Copyright (c) 2024 2024-07-04 2024-07-04 5 2 e5463 e5463 10.54021/seesv5n2-012 Enhancing doubly-fed induction generator performance in wind energy systems using intelligent control <p>This study investigates the optimization of doubly-fed induction generator (DFIG) performance in wind energy systems using intelligent control techniques. The research focuses on two primary control methods: fuzzy logic and artificial neural networks, complemented by neural space vector modulation (NSVM) for enhanced power quality. The paper presents a comprehensive model of the wind energy conversion chain and vector control of the DFIG, with particular emphasis on improving active and reactive power control. Simulation results demonstrate the effectiveness of both fuzzy logic and neural network systems in tracking power changes. However, the neural network-based control exhibits superior performance in reducing current and electromagnetic torque ripples. a key aspect of the study is the total harmonic distortion (THD) analysis of the source current. the neural network system achieves a lower THD value (0.11%) compared to the fuzzy logic system (0.32%), indicating better power quality. additionally, a robustness test involving alterations to generator parameters reveals the fuzzy logic system's greater adaptability to these changes. the research also explores the implementation of space vector modulation (SVM) based on neural networks (NSVM) to replace conventional switching pulse-width modulation (PWM) techniques. This approach significantly improves power quality and enhances performance in the presence of machine parameter variations. The study concludes by highlighting the potential of these intelligent control techniques in improving wind energy system performance. it provides valuable insights for developing more efficient and reliable control systems for DFIG in wind energy applications. The findings contribute to ongoing efforts to enhance renewable energy efficiency and reliability, potentially accelerating the adoption of wind power in the global energy mix.</p> Abdelmoumen Chandad Messaoud Hamouda Mohammed Bouzidi Omar Ouledali Copyright (c) 2024 2024-07-04 2024-07-04 5 2 e5464 e5464 10.54021/seesv5n2-013 The influence of the piezoelectric effect on stress distribution in semiconductor layers <p class="referencias" style="text-align: justify;">This study investigates thin structures by analyzing stress distribution in two different scenarios. In the first scenario, the absence of the E<sub>3</sub> and d<sub>31</sub> parameters is considered, while the second scenario examines their influence. The parameters vary according to a mixing rule based on thickness, with h<sub>1</sub>, h<sub>2</sub>, and h<sub>3</sub> representing the distinct layers of the structure. The coordinate origin is positioned on the lower surface of the structure. The piezoelectric effect in semiconductor layers refers to the phenomenon where mechanical stress within the material generates an electric charge due to the inherent piezoelectric properties of the material. This effect significantly influences the stress distribution in semiconductor layers, altering their mechanical and electrical behavior. Understanding this impact is crucial for optimizing the design and performance of semiconductor devices, as it affects the material's ability to handle stress and distribute it evenly, thereby enhancing the reliability and efficiency of electronic components. This comparative analysis enhances the understanding of the piezoelectric effect on stress distribution in semiconductor layers. By comparing these two scenarios, significant differences in stress distribution are observed when piezoelectric effects are considered. Understanding how piezoelectric effects influence stress distribution aids engineers in designing better semiconductor layers, enhancing both performance and reliability. This research underscores the critical importance of considering piezoelectric effects in the design and analysis of thin structures. By incorporating these effects, engineers can develop semiconductor devices that are not only more efficient but also significantly more robust. The study's findings highlight the necessity of integrating piezoelectric considerations into engineering practices to optimize material properties and structural integrity, ultimately leading to advancements in semiconductor technology and contributing to the development of high-performance, reliable electronic devices.</p> Zine Abdallah Berrabah Hamza Madjid Bouderba Bachir Copyright (c) 2024 2024-07-04 2024-07-04 5 2 e5465 e5465 10.54021/seesv5n2-014 Development of generalized photovoltaic model using ISIS-PROTEUS <p class="referencias" style="text-align: justify;"><span style="letter-spacing: -.1pt;">Photovoltaic (PV) energy is a form of renewable energy that generates electricity from sunlight. PV systems consist of solar cells, which convert sunlight into electricity using a process known as the photovoltaic effect. Modeling and simulating PV systems involves using mathematical and computational models to predict the behavior and performance of PV systems under various conditions. This can include modeling the electrical characteristics of solar cells, as well as the interactions between multiple cells in a PV module or system. Following this sense, we present in this work a novel implementation of a generalized PV model using ISIS Proteus software. Proteus is layout software for electronic circuit simulation, schematic capture and PCB design. Some studies have indeed taken this context to model the PV modules either by using a Proteus Spice model of the photovoltaic panel without including the effect of climatic conditions variation, or by using pure mathematical relations that describe all physical and environmental parameters which will lead to a static behavior. The developed model in this paper as it is generalized, can be typically used as a PV cell, module even a generator for a complete simulation of a PV system. PV cell, which is the elementary component of PV system, is modeled using the single diode equivalent circuit (SDM) also known as five-parameter model and its behavior is simulated in details. The most advantage in our study is the fact that the PV output can be obtained wherever what solar radiation and ambient temperature where PV module is operating. Our model gives also the possibility to simulate a dynamic behavior under any climatic conditions. The accuracy between obtained results of simulation and the experimental data confirm the reliability and the high performance of the developed model.</span></p> Alaeddine Ahmed Azi Djamel Saigaa Mahmoud Drif Abdelouadoud Loukriz Copyright (c) 2024 2024-07-08 2024-07-08 5 2 e5546 e5546 10.54021/seesv5n2-015 An ultra-wideband antenna design optimization for biomedical applications using artificial neural networks <p>This paper presents an innovative method based on Artificial Neural Networks (ANN) for optimizing the design of microstrip antennas using HFSS software. The method leverages a dataset generated from comprehensive full-wave electromagnetic simulations to accurately predict antenna performance. In the ANN model, &nbsp;coefficients of reflection as&nbsp; input parameter, and five output parameters representing key geometrical variables of the antenna are utilized. The study demonstrates how ANNs effectively predict these variables, thereby enhancing design efficiency and significantly reducing the computational time required for antenna optimization. By providing a robust and efficient framework, the results highlight the promising potential of ANNs in optimizing antenna designs for diverse applications, including medical and wireless communication systems. Specifically, the proposed Ultra-Wideband (UWB) antenna operates over a frequency range from 5.17 GHz to 7.02 GHz and maintains an S11 value of -20.49 dB at 5.8 GHz within the Industrial, Scientific, and Medical (ISM) bands. This research contributes valuable insights into advancing electromagnetic performance through efficient antenna design methodologies.</p> Rania Ibtissam Benmelouka Yamina Tighilt Kamil Karaçuha Abdelhak Ferhat Hamida Asma Slimani Copyright (c) 2024 2024-07-08 2024-07-08 5 2 e5547 e5547 10.54021/seesv5n2-016 Prediction and interpretation of limit pressure of clayey soils using ensemble machine learning methods and shapely additive explanations <p>The pressuremeter test (PMT), a valuable geotechnical in situ test, is used to design foundations of varying depths (shallow, semi-deep, and deep). It assesses a soil's bearing capacity and settlement through two key parameters: limit pressure and pressuremeter modulus. However, the high cost and time demands of PMTs limit their widespread use. This study addresses this challenge by exploring the effectiveness of ensemble machine learning algorithms. To achieve this main goal, we employ two methods, Extreme Gradient Boosting (XGBoost) and Random Forest, to predict limit pressure of soil. To develop the mentioned models an experimental database was used to train and validate the developed models.<strong>&nbsp; </strong>The effectiveness of these methods are evaluated using three statistical metrics: Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Coefficient of Determination (R²). The performance metrics show that the developed XGBoost and Random Forest models are viable alternatives to the pressure meter test for estimating limit pressure. Both models achieved high R-squared values (around 0.99 for training and 0.90 for testing) and a low root mean squared error (RMSE) of 3.23 and 4.13 for the testing set, respectively. These results demonstrate the effectiveness of using machine learning in the geotechnical field. To further understand the influence of individual factors on the predictions, we will utilize the Shapley Additive explanations (SHAP) method. This technique analyzes the contribution of each input variable (feature) to the model's predictions of limit pressure. By quantifying the importance of these features; SHAP provides valuable insights into which soil properties most significantly affect the foundation design parameters.</p> Kamel Goudjil Ghania Boukhatem Ridha Boulifa Souhila Rehab Bekkouche Djelailia Djihane Copyright (c) 2024 2024-07-09 2024-07-09 5 2 e5567 e5567 10.54021/seesv5n2-017 Predictive modeling of aramid fiber reinforced polymer confinement for improved compressive strength in circular concrete columns <p>Fiber Reinforced Polymers (FRPs) have gained significant attention in the field of structural engineering due to their high strength-to-weight ratio, corrosion resistance, and ease of application. Among various types of FRPs, Aramid Fiber Reinforced Polymers (AFRP) stand out for their exceptional tensile strength and durability, making them ideal for confining concrete columns to enhance their compressive strength. This study aims to leverage these benefits by predicting the compressive strength of circular concrete columns confined with AFRP using Artificial Neural Networks (ANNs). To develop and validate the ANN model, a comprehensive dataset consisting of 190 samples was employed during the training phase, while an additional set of 33 samples was used for validation. The performance and predictive capabilities of the ANN model were thoroughly assessed through extensive testing and direct comparison with experimental results, which demonstrated the model’s high accuracy and reliability. Moreover, a detailed parametric study was conducted to examine the influence of various input parameters on the compressive strength prediction. The findings from this study offered significant insights into the effects of various parameters on the predicted outcomes, including column diameter, unconfined concrete strength and strain, as well as AFRP confinement parameters such as thickness, tensile strength, elastic modulus, and strain. Notably, the sensitivity analysis underscored the profound impact of the tensile strength of AFRP on the ANN model's predictive accuracy. The research offers a robust tool for engineers, enabling them to estimate the compressive strength of AFRP-confined circular concrete columns accurately. Additionally, it provides crucial insights that are instrumental in optimizing the design and application of AFRP wrapping or tube-encased methods within the realm of structural engineering. Overall, this research marks a significant step forward in the field of structural engineering, providing a valuable predictive tool and offering insights that can lead to the development of more resilient and sustainable infrastructure.</p> Imane Djafar-Henni Amina Sadouki Copyright (c) 2024 2024-07-09 2024-07-09 5 2 e5582 e5582 10.54021/seesv5n2-018 Predicting project duration using a coupled artificial neural network and Taguchi method approach <p class="referencias" style="text-align: justify;">Accurate project duration prediction is increasingly important for management because it defines the expected timeline for project realization. This study utilizes an integrated approach combining neural networks with the Taguchi method to forecast the time required to complete projects within predetermined deadlines. The methodology involves modelling and simulating the network of project activities to estimate the total average project duration. ration. The neural network model uses input variables such as success probability, effort, and learning factor to predict the total time necessary for project completion. The total average project duration is the output variable that is critical during the design phase. Subsequently, the Taguchi method optimizes the neural network’s outputs, incorporating mean squared error (MSE) values to enhance predictive accuracy. accuracy. This study underscores the efficacy of artificial neural networks (ANNs) as predictive tools, demonstrating their ability to meticulously estimate project duration. The proposed method’s efficiency and applicability are demonstrated by MATLAB simulation analyses, highlighting its effectiveness in precise deadline estimation. In the realm of engineering, ANNs stand tall as formidable predictive tools, their efficacy underscored by this study’s successful application. By harnessing ANNs and simulation data, this research crafts a predictive model adept at estimating the average total duration of projects. Through meticulous consideration of crucial parameters like the probability of success and effort factors, the model emerges as a beacon of accuracy within the design domain. Future research will explore the effects of additional parameters on activity networks and alternative transfer functions, as well as the potential integration of reinforcement algorithms to improve resource allocation, risk management, and project outcomes through online training data.</p> Larbi Bendada Mourad Brioua Mohamed Razi Morakchi Ibrahim Djouani Copyright (c) 2024 2024-07-11 2024-07-11 5 2 e5641 e5641 10.54021/seesv5n2-019 Seismic vulnerability assessment of tunnels in algeria: An innovative hierarchical approach <p>Tunnels are crucial components of civil infrastructure, serving as vital transportation routes for the public. In Algeria, where many tunnels are located in seismic zones, they face considerable risks from earthquakes, which can potentially impair their operational integrity. The susceptibility of these tunnels to seismic hazards underscores the need for robust assessment frameworks to evaluate their vulnerability. This study introduces a novel hierarchical framework for assessing tunnel vulnerability, drawing on global seismic data and experience. By integrating the Analytic Hierarchy Process (AHP) with the Vulnerability Index (VI), we categorized tunnels into three vulnerability levels. This approach enabled the development of seismic scenarios to forecast their performance during future earthquakes. The methodology was applied to numerous tunnels across Algeria, yielding insightful results that align with observations from post-seismic assessments. By systematically analyzing various influencing parameters, including geological conditions, structural design, and operational factors, the study enhances our understanding of tunnel resilience in seismic contexts. Ultimately, this research contributes to proactive risk management strategies for tunnel infrastructure, aiming to mitigate potential damages and ensure their continued functionality in earthquake-prone regions like Algeria. By refining our assessment methods and predictive capabilities, we strive to bolster the resilience of critical urban infrastructure against seismic risks.</p> Zakaria Ghribi Mahmoud Bensaibi Copyright (c) 2024 2024-07-11 2024-07-11 5 2 e5665 e5665 10.54021/seesv5n2-020 Transmission problem between two Bingham fluids in a tow dimensional thin layer <p>The paper focuses on studying the asymptotic behavior of the steady-state transmission problem between two Bingham fluids in a two-dimensional thin layer. We are interested in the asymptotic behavior, to this aim we prove some convergence results concerning the velocity and pressure when the thickness tends to zero. The limit problem obtained after transforming the original problem into one posed over a fixed reference domain and the parameter representing the thickness of the layer tend to zero is studied. The lower-dimensional constitutive law and the differential equation satisfied by the limit variables in the non rigid zone are obtained. In addition, the uniqueness of limit solution has been also established. Existence and uniqueness results and a lower-dimensional constitutive law are obtained.</p> Salim Saf Farid Messelmi Copyright (c) 2024 2024-07-15 2024-07-15 5 2 e5757 e5757 10.54021/seesv5n2-021 Predictive control of a series-connected two five-phase synchronous magnet permanent machines <p>The work presented in this paper focuses on studying the concept of two five-phase permanent magnet synchronous machines connected in series, powered by a single five-arm converter, in order to considerably minimize circulating currents. Firstly, we modeled a system composed of two identical five-phase synchronous machines, whose stator windings are connected in series. This modeling aims to demonstrate that the control of each machine in the group can be independent of the other, even though both machines are powered by a single five-phase converter. Then, we carried out the predictive control of the two five-phase machines connected in series. This control is based on the prediction of future switching states, which are managed via the discrete model of the system. The optimal switching state is obtained according to a predetermined cost function. To demonstrate the features of the presented control algorithm, the results of the simulation conducted using MATLAB/Simulink are presented and discussed to evaluate the performance and efficiency of the independent control of the two five-phase synchronous machines connected in series.</p> Abdesslam Ouanouki Katia Kouzi Djamel Difi Mohamed Ghibeche Copyright (c) 2024 2024-07-15 2024-07-15 5 2 e5758 e5758 10.54021/seesv5n2-022 Mechanical behavior of calcareous tuff and coal mine tailings mixture as an embankment material for road construction <p>The construction of embankments requires available and suitable material that sounds to the imposed load. The selection of materials that provide slope stability and maintain pavements is made through specific test control. This research aims to analyze the mechanical behavior of a mixture of 75% calcareous tuff and 25% coal mine tailings (CMTs) used on embankment&nbsp;foundations. the impact of particle size characteristics and the compaction on the mechanical behavior of the mixture are studied. The direct shear test was conducted on different material states, granular and uncompressed states, compaction at the Maximum Practical Optimum (MPO), and MPO compaction post a 30-day curing period at 40 degrees Celsius. the normal stress applied ranging from 50 to 500 KPa, with a constant shear rate displacement of 0.5 mm/min. The results show a substantial influence of compaction on both friction angle (φ) and cohesion (C) values. a remarkable increase in cohesion values after the curing period, attributed to the cementitious compound formation from the interaction between calcareous tuff and coal mine tailings. This investigation emphasizes coal mine tailings potential as a sustainable and cost-effective embankment material for road construction, especially in arid regions. The material exhibits significant shear strength, with a marked increase in cohesion values post-curing state. These results are conducted to consider coal mine tailings as an appealing alternative to traditional materials of road engineering.</p> Oussama Khodjet El Fehem Nabil Bella Amel Boudia Copyright (c) 2024 2024-07-15 2024-07-15 5 2 e5759 e5759 10.54021/seesv5n2-023 Inspection of aluminum sheets using a multi-element eddy current sensor: 2d and 3d imaging of surface defects of various sizes and internal defects at various depths <p class="referencias" style="text-align: justify;">In the industrial sector, ensuring reliability and durability is of paramount importance. Our research aims to advance beyond conventional non-destructive testing methods by focusing on thorough defect detection and imaging. We utilize advanced, sensor-enhanced eddy current testing, featuring multiple elements arranged in a cutting-edge serial array. This innovative configuration addresses the issue of magnetic repulsion between sensor elements, thereby speeding up the testing process and ensuring precise results through both 3D and 2D imaging. This sophisticated approach allows us to more effectively characterize defects of varying sizes and depths in aluminum sheets. By meticulously collecting and analyzing data from the sensors, we can identify the appearance and nature of these defects with greater clarity. Our findings introduce a pioneering method for defect detection, highlighting the efficacy of our advanced testing technique. Our research underscores the potential of multi-element eddy current sensors in revolutionizing the inspection process. The ability to produce detailed 3D and 2D images of surface and internal defects represents a significant leap forward in non-destructive testing. This comprehensive imaging capability not only accelerates the detection process but also enhances the accuracy and reliability of defect characterization. By employing this state-of-the-art technology, we can detect even the smallest and most deeply embedded defects that traditional methods might miss. The precise imaging provided by our approach ensures that defects of various sizes and depths are accurately identified and characterized. This level of detail is crucial for maintaining the structural integrity and performance of aluminum sheets used in industrial applications. Our research demonstrates a groundbreaking approach to defect detection in aluminum sheets, leveraging the advanced capabilities of multi-element eddy current sensors. The innovative use of a serial array of sensors, combined with sophisticated data analysis techniques, allows for rapid, accurate, and detailed imaging of defects. These findings pave the way for improved reliability and durability in industrial applications, setting a new standard for non-destructive testing.</p> Abderrahmane Aboura Abdelhak Abdou Tarik Bouchala Merwane Khebal Bachir Abdelhadi Amor Guettafi Copyright (c) 2024 2024-07-16 2024-07-16 5 2 e5786 e5786 10.54021/seesv5n2-024 Efficient mathematical methods for modeling and simulating adsorption of copper (II) on activated carbon utilizing date nuts <p>In our research, we demonstrate the application of mathematical methodologies to analyze the retention efficiency of Cu<sup>2+</sup> cations through adsorption on powdered activated carbon derived from date nuts. Due to the growing importance of copper elimination in environmental spheres, there is a need for accurate simulation and prediction techniques. The investigation emphasizes the significance of numerical methods in improving simulation precision. The integration of optimization strategies and numerical approaches offers a comprehensive predictive framework for copper adsorption on activated carbon. By utilizing initial parameters as inputs, the Matlab algorithm proposed by Hassouna in this study is employed to simulate the adsorption mechanisms, with the resultant outputs encompassing the nature of adsorption (isotherms, kinetics). The findings results the effectiveness of the methodologies employed in this research. Moreover, experimental assessments indicate that optimal efficiency is achieved at equilibrium after 90 minutes for activated carbon derived from date nuts. This computational methodology streamlines the effective handling of empirical data to protect the environment from contaminants such as Cu<sup>2+</sup> cations&nbsp; in a manner that is both uncomplicated and time-efficient.</p> Houda Hassouna Hanane Rehali Khaled Athmani Siham Djebabra Fedia Bekiri Copyright (c) 2024 2024-07-16 2024-07-16 5 2 e5787 e5787 10.54021/seesv5n2-025 Predicting the modulus of elasticity of clayey soil composites reinforced with scrap tire rubber fibers using a composite material model <p class="referencias" style="text-align: justify;">In this study, composite material models are used to predict the modulus of elasticity of a composite consisting of scrap tire rubber fibers and clayey soils. The calculated modulus of elasticity is compared with the reference modulus obtained from experimental testing. Predicting the effective mechanical properties of composites is crucial in situations where testing is impractical, challenging, or costly. The analysis involves various approaches within the elasticity framework, utilizing rheological models such as Voigt, Reuss, Hirsch-Dougill, Popovics, Halpin-Tsai, Hashin, and the Bache &amp; Napper–Christensen estimation. These models aim to predict the effective Young's modulus of the composite system comprising soil and rubber fibers. The maximum discrepancies observed are 10.66%, 12.71%, and 12.98% for both soils. Voigt, Hashin, and Bache estimations provide highly accurate predictions of the effective Young's modulus, showing excellent agreement with experimental results across different fiber volume fractions ranging from 10% to 50%.</p> Melik Bekhiti Copyright (c) 2024 2024-07-16 2024-07-16 5 2 e5788 e5788 10.54021/seesv5n2-026 Study of the adsorption mechanism of certain dyes from wastewater on commercial activated carbon using the Langmuir and Freundlich methods <p>In today's society, there is significant emphasis on environmental protection, with research focused on reducing pollution and developing effective depollution techniques. A growing concern is the presence of colored discharges in wastewater, which contain high levels of toxic substances that pose substantial risks to ecosystems. To mitigate these risks, various methods are employed to remove pollutants from industrial effluents, with adsorption being one of the most effective. Among the adsorbents used, activated carbon is the most commonly utilized due to its high surface area and adsorption capacity. This study aims to enhance the understanding of how two organic dyes, Methyl Red and Methylene Blue, can be removed from aqueous media through adsorption onto commercial activated carbon. The adsorption kinetics and isotherms were employed to elucidate the mechanisms involved in the elimination of these dyes from water. The kinetics were investigated using a stirred reactor, with experiments designed to vary parameters such as the initial dye concentration, the mass of the adsorbent, and the contact time. The experimental data were modeled using kinetic equations of first and second order. The results indicated that the adsorption of both Methyl Red and Methylene Blue onto activated carbon followed a pseudo-second-order kinetic model, as evidenced by large regression coefficients, signifying a good fit. This suggests that the adsorption process is likely controlled by chemisorption, involving valency forces through sharing or exchange of electrons between adsorbent and adsorbate. Additionally, the adsorption isotherms were analyzed to further understand the adsorption mechanisms and capacity. The results showed that the adsorption of both dyes onto commercial activated carbon conformed well to the Freundlich isotherm model. This model implies that adsorption occurs on a heterogeneous surface with a non-uniform distribution of adsorption heat over the surface. Overall, this study provides valuable insights into the adsorption behavior of Methyl Red and Methylene Blue on activated carbon, highlighting the effectiveness of this adsorbent in removing organic dyes from wastewater. The findings underscore the potential of using commercial activated carbon in the treatment of industrial effluents, contributing to the development of more efficient and sustainable water purification methods.</p> Yasmina Mokhbi Zineb Ghiaba Zineb Akchiche Rebha Ghedamsi Bakhta Recioui Copyright (c) 2024 2024-07-16 2024-07-16 5 2 e5789 e5789 10.54021/seesv5n2-027 Correlation between destructive and non-destructive evaluation to study of plastic waste aggregate mortar: a case study of mechanical proprieties <p>Non-destructive evaluation using ultrasonic pulse velocity (UPV) testing has extensive applications in the cement materials industry. Ultrasonic pulse velocity (UPV) test is accepted as alternative to destructive testing to determine the compressive strength, dynamic modulus of elasticity, and Poisson’s ratio, which are needed for structural design. In modern construction technology, the use of Plastic waste (PW) as a partial replacement to natural aggregates in a mortar mix is growing in popularity primarily because it reduces the initial capital cost of raw materials and the associated conservation in environment. In this regard, this study explains the correlations between mechanical proprieties, and UPV tests for mortar contains 25%, 50%, and 75% of waste aggregate of plastic.&nbsp;&nbsp; Mortar based on Plastic Waste (MPW) specimens were tested by direct, semi-direct, and indirect UPV. UPV measurements can be effectively used to determine the dynamic modulus of elasticity and Poisson’s ratio of Mortar based on Plastic Waste&nbsp;&nbsp; MPW. The dynamic elastic modulus and the Poisson’s ratio decreases for the same mortar composite when at increasing PW content. Thus, the incorporation of PW particles into the cement matrix confirms the capacity of composites to reduce the sound intensity and damp vibrations inside the composites. The results of this study will be significant for non-destructive evaluations of MPW, while additional recommendations for future studies are presented at the end of the paper.</p> Ahmed Soufiane Benosman Abdelhak Badache Omar Safer Mouloud Dahmane Mostefa Hacini Mohamed Mouli Mourad Benadouda Copyright (c) 2024 2024-07-16 2024-07-16 5 2 e5790 e5790 10.54021/seesv5n2-028 A new magneto-plastic coupling model for residual stress description in ferromagnetic materials <p>The paper addresses the topic of residual stress in magnetic behaviour of the ferromagnetic materials. Carbon steel parts are submitted to several stress loads and the magnetic behaviour is collected at several operating points. After stress load, the hysteresis data are measured and illustrate a complex behaviour in hysteresis morphology where a big belly is observed near coercive field and a short neck in maximum induction zone. In order to describe the B-H curves, a modified Arctangent model is proposed. A comparison between experiments and model signals show a very good accuracy.</p> Ahmed Nait Ouslimane Yasmine Gabi Copyright (c) 2024 2024-07-16 2024-07-16 5 2 e5792 e5792 10.54021/seesv5n2-029 Ab-initio prédiction of the structural ,electro-magnetic and thermodynamic properties of Co-based Full Heusler alloy <p>The structural, thermodynamic, electronic, magnetic and elasticproperties of the Full-Heusler Co<sub>2</sub>MnTi compoundon the cobalt (Co) are determined byusing first-principles calculations based on density functional theory (DFT). We have used the linear Muffin-Tin Orbitals method (FP-LMTO) combined with the generalized gradient approximation (GGA) with spin. The obtained results demonstrate that our material is ferromagnetic and exhibits metallic behavior around the Fermi level .The study of the elastic properties show that Co<sub>2</sub>MnTi is mechanically stable and is also classified as a ductile material. The GIBBS program is used to comput the thermodynamic properties such as the modulus of compressibility, the heat capacity volume and pressur, the thermal expansion, the Debye temperature and the volume variation at constants. This type of material is considered as promising for spintronic applications.</p> Loubna Bellagoun Fatima Zohra Boufadi Amal Mentefa Feriel Ouarda Gaid Copyright (c) 2024 2024-07-16 2024-07-16 5 2 e5793 e5793 10.54021/seesv5n2-030 Numerical investigations of GRS wall performance with tiered configurations <p>Geosynthetic Reinforced Soil (GRS) walls have become increasingly popular as a result of their numerous advantages. In some cases these structures are constructed in a multi-tiered configuration, which makes their behavior more complicated. Nevertheless, the response of the multi-tiered walls is insufficiently explained by the existing design manuals and literature studies. This paper investigated the performance of GRS walls with multi-tiered configurations using two-dimensional (2D) finite element numerical models. This study compares the performance of two-tiered GRS walls with simple GRS walls (single-tiered). It also examines the impact of offset distance, backfill strength properties, and reinforcement parameters (vertical spacing and reinforcement length) on horizontal deformations and reinforcement tensile loads in two-tiered GRS walls. Adopting a multi-tiered configuration for GRS walls can significantly reduce both the horizontal wall deformation and the maximum reinforcement tensile loads. Additionally, the critical offset distance found in this study is significantly smaller than that recommended by the Federal Highway Administration (FHWA) guidelines. The finite element results also demonstrate that using high-quality backfill soil can minimize interaction between lower and upper tiers. Using a uniform reinforcement length of 0.6H for both tiers significantly reduces horizontal deformation compared to the FHWA recommendation of 0.6H and 0.35H for the lower and the upper tier respectively.</p> Farik Ali Sadok Benmebarek Mohamed Djabri Copyright (c) 2024 2024-07-17 2024-07-17 5 2 e5857 e5857 10.54021/seesv5n2-031 Mechanical properties and durability evaluation of self-compacting mortars containing glass and brick powders <p>The present Paper examines the mechanical properties and some durability aspects of self-compacting mortars (SCM) with Glass (GP) and Brick Powders (BP) at different cement replacement levels, along with different finenesses. The mechanical properties that have been evaluated by compressive and flexural strength tests at the ages of 07, 14, 28, 56, 90 and 400 days, shrinkage tests, alkali-silica reaction (ASR), microstructure and high temperature strength tests of 90-day cured SCM, exposed to 400°C, 600°C and 800°C, have been conducted. The results indicated that SCM with Glass Powder (SCM-GP) and Brick Powder (SCM-BP) have showed an improvement in compressive and flexural strengths with increasing fineness, and alike with the curing age compared to the control SCM. Likewise, the drying shrinkage of SCM-GP has significantly reduced with the addition of GP, whilst the shrinkage increased for SCM-BP, with the increase of BP, but still remained lower or equal to the one relating to the control SCM. This study has alike showed that the expansion following the alkali-silica reaction for SCM-GP at 24% GP, and SCM-BP at 20% BP, was significantly lower than the control mixture; further, the reduction is 54% and 64% respectively compared to the control mixture. But also, the SCM with GP and BP showed better performance in terms of high temperature resistance. This study brings to light the possibility of producing ecological cementitious composites from waste glass and calcined brick, as a partial replacement for Portland cement.</p> Yasmina Bouleghebar Mohamed Bentchikou Otmane Boukendakdji Copyright (c) 2024 2024-07-18 2024-07-18 5 2 e5864 e5864 10.54021/seesv5n2-032 Optimizing record linkage with Firefly algorithm and LSH <p>Identifying record linkage, the task of identifying and linking records that correspond to the same real-world entity across multiple databases, is a critical component of data management. The accuracy of this process is crucial to ensure the integrity and consistency of information within various applications. Unsupervised blocking methods have gained popularity for their ability to handle large-scale and complex datasets without relying on labeled data. These methods overcome the limitations of traditional supervised approaches by offering greater flexibility and adaptability. This article introduces an innovative approach to record linkage, addressing the critical task of linking records across multiple databases. Implementing unsupervised blocking methods, we propose a novel integrated method using the Firefly Algorithm and Locality Sensitive Hashing (LSH). This approach leverages the combined strengths of these techniques to improve the linkage process. The methodology includes comprehensive data pre-processing with length-based feature weighting (LFW), ensuring that the most relevant features are retained for linkage. The Firefly Algorithm, inspired by the natural flashing behavior of fireflies, optimizes feature selection for more relevant clustering, while LSH aids in dimensionality reduction and efficient candidate generation by hashing similar records into the same buckets with high probability, significantly reducing the number of comparisons needed. Experimental evaluations on various real-world datasets demonstrate the effectiveness of our approach in achieving high-quality record linkage results. The results indicate that our method not only improves linkage accuracy but also significantly reduces computational time compared to traditional methods. Additionally, we explore the potential for scaling this approach to big data environments, addressing challenges related to efficiently processing large volumes of data. This scalable solution paves the way for its application in various fields such as healthcare, finance, and e-commerce, where accurate record linkage is paramount.</p> Aissam Bendida Amar Bensaber Djamel Réda Adjoudj Yahia Atig Copyright (c) 2024 2024-07-18 2024-07-18 5 2 e5881 e5881 10.54021/seesv5n2-033 Air cooling condenser simulation and numerical modeling in a steady-state <p>Due to their crucial significance in cooling equipment, air-cooled condensers have been extensively studied in scientific studies to increase their quality and efficiency. The refrigerant fluid travels via three different locations in the condenser. First, a single-phase fluid flow has overheated gas at the compressor outlet. Subsequently, a two-phase fluid with a gas and a liquid component flows. In the end, the liquid moves in a single phase. This study is predicated on the fluid's compressibility and the fixed diet in the three circumstances. The heat and mass transport phenomena between liquid and vapor in the flow zone are explained via condenser modeling. The equations that control this flow are the enthalpy air equation, the energy equation applied to the tube wall, the conservation equation of mass, quantity of motion, and energy plus. Using the Refprop V8.0 subroutines and the Fortran code, we computed the fluid's properties for the numerical resolution. This study aims to investigate and improve the condenser's efficiency.</p> Ahmed Haidour Achour Mansouri Hamou Soualmi Boumedien Touati Copyright (c) 2024 2024-07-18 2024-07-18 5 2 e5882 e5882 10.54021/seesv5n2-034 Editorial – v. 5, n. 2 <p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</p> Bárbara Bonfim Copyright (c) 2024 STUDIES IN ENGINEERING AND EXACT SCIENCES 2024-07-02 2024-07-02 5 2