Ecole Nationale d'Ingénieurs de Monastir

Additive manufacturing, especially Fused Deposition Modelling (FDM), is increasingly adopted for producing functional end-use products. However, a key limitation of FDM is the build chamber size, which restricts the maximum dimensions of 3D-printed parts. This constraint impacts the stability, deformation and cost of the final product. To overcome this, larger components are often assembled from smaller parts, with adhesive bonding presenting a viable solution for joining these subassemblies. This study investigates how combining atmospheric-pressure plasma (APP) treatment with various surface patterns affects the surface properties and shear strength of 3D-printed polycarbonate joints. Four types of surfaces were examined: as-printed, polished (P1000), FS (fish scales), and TF (tree frog) textures. The findings reveal that APP treatment improve shear strength for P1000 and as-printed surfaces by 37% and 22%, respectively, due to the formation of polar functional groups that enhance surface wettability and adhesive bonding. However, FS and TF bio-textures show no additional strength improvement after APP treatment, likely due to their already strong mechanical interlocking. Additionally, the non-treated TF joint, which had the highest shear strength among all tested joints, has demonstrated a shear resistance of 21% lower than that of the fully 3D-printed specimen. This indicates that incorporating an appropriate surface pattern, such as TF, directly into the 3D printing process of the parts to be assembled can achieve joint strength comparable to that of a fully 3D-printed component without additional treatments.

Due to geographical and infrastructure limitations, the rural parts in many countries have difficulty obtaining sustainable and dependable energy. The goal of this research is to develop and improve an integrated hybrid renewable energy system (HRES) that can generate heat, hydrogen, and electricity all at once for off-grid uses. Fuel cells, diesel generators, electrolyzers, solar panels, and reformers are all combined to create a unique system. The HOMER software platform is used to improve the system configuration in order to reduce the overall net present cost while maintaining a dependable energy supply. An 80 kW fuel cell, a 100 kg/hr reformer, a 100 kW diesel generator, a 3,500 kW electrolyzer, and 6.9 MWp of PV panels make up the optimized HRES. With a levelized hydrogen cost of 4.2 €/kg, the system produces around 307,832 kg of hydrogen, 257.86 MWh of heat, and 13.45 GWh of electricity yearly. A workable approach to distant electrification is the combination of hydrogen production and storage with renewable energy. By reducing dependency on fossil fuels, this strategy not only improves energy security but also lessens environmental effects.

Anti-control and synchronization of period doubling and chaos is a method for bifurcation control. It can be used to detect the occurrence or periodic behavior of a bifurcation at the specified position to meet the requirements of brushless direct current (BLDCM). Antichaotic control can be implemented through the use of an external periodic term or constant. The study of the parametric singularities of brushless direct current (BLDCM) allows the identification of a complex bifurcation structure, namely the limit point (LP), the Hopf (H) and the Bogdanov-Takens (BT) bifurcations, the period-doubling bifurcation and path to chaos . By adjusting the control parameters of the controller, the period doubling bifurcation can be generated or suppressed at the specified position to realize the anti-control of period doubling and chaos bifurcation. Parametric singularities are analyzed using a variety of anti-control signals, including constant voltage, periodic square, sawtooth wave, triangle, etc. The simulation results show that adding constant or periodic factors improves chaos and anti-control effects.

This paper examines the key factors influencing the relationship between domestic energy consumption and renewable energy adoption in Tunisia, based on a survey of 1000 participants from various sectors, including students, teachers, and social media users. The findings reveal that while 65% of households report high energy consumption, mainly due to heating and air conditioning, only 35% have adopted energy-efficient technologies. Although 80% express concern about climate change, only 45% understand the connection between personal energy use and environmental impact. Additionally, 70% of respondents show a positive attitude toward solar energy, but 60% cite installation costs as a significant barrier. The paper focuses on the potential of positive energy communities (PECs), particularly in rural areas, where 75% of respondents showed interest. The study emphasizes the need for a comprehensive strategy combining education, policy frameworks, and community-driven energy solutions to reduce consumption and increase renewable energy use. Concrete recommendations are provided to support a sustainable energy transition in Tunisia, with a focus on enhancing energy autonomy and environmental preservation through PECs.

Lower urinary tract symptoms (LUTS), particularly urinary incontinence (UI), represent a significant global health challenge, affecting millions of patients worldwide. The artificial urinary sphincter (AUS) remains one of the most effective intervention for severe UI, with its design relying on a detailed understanding of the urethral biomechanics. Given the ethical and logistical constraints of using human tissue, porcine urethras, which share anatomical and mechanical similarities with human urethras, are widely employed in preclinical studies. This study investigates the uniaxial mechanical characterization of porcine urethral tissue under controlled conditions. Fresh porcine urethral samples were subjected to uniaxial tensile testing along both the longitudinal and circumferential directions to characterize their anisotropic mechanical properties. Experimental results were compared with existing datasets to validate findings. Additionally, conventional hyperelastic models were assessed to fit experimental results, and a novel anisotropic constitutive model with physical parameters was developed. This fiber model, which incorporates fiber modulus, volume, and orientation, uses a single set of parameters to predict behavior in both directions. It demonstrated improved accuracy, reaching the performance of the Gasser-Ogden-Holzapfel (GOH) model, with root mean square errors (RMSEs) of 9.24% and 12.98% in the circumferential and longitudinal directions, respectively. In contrast, the Yeoh and Ogden models were unable to fit both directions using a single set of parameters, yielding RMSEs values exceeding 30%. With its enhanced physical relevance, the fiber model having a more physical meaning holds promise for applications in the biomechanical analysis of fiber-composed soft tissues.

The global development of LED lighting in all applications for both public and indoor lighting establishes a very important lever for reducing the carbon impact by significantly reducing energy consumption. Smart lighting will therefore constitute an essential lever in the smart city of tomorrow. The latter is more sustainable and less energy-intensive than other light sources, contributing towards the Sustainable Development Goals set forth by the United Nations (SDGs 7 and 11). With its ease of integration, ergonomics, lightness, and high quality of light, this innovative light source has two major qualities: its energy efficiency and its long service life. However, poor thermal management has catastrophic effects on these two essential criteria. This necessarily requires optimizing thermal management and heat sinks. In some cases, thermal models and simulations can lead to considerable calculation times because they implement many parameters. This work therefore aims to reduce the number of these simulations by applying the method of experimental designs (Taguchi) and analysis of variance (ANOVA) to simulations intended to optimize the dissipation of LED luminaires. We applied the method to a simple finned heat sink model for a unit input power and then to a concrete case of a high-power LED. The control parameters and their respective contributions in the proposed model were studied. The ANOVA results corroborated the conclusions of the Taguchi method, demonstrating a strong agreement between these analytical methods, in which the temperature was adjusted by identifying optimal combinations of parameters. The fields of application relevant to this study include both indoor lighting (false ceiling) and confined spaces with severe sealing constraints such as car headlights or the optical blocks of urban luminaires.

In this article we study, from the numerical point of view, a problem involving an extensible thermoelastic beam with microtemperatures derived recently by Aouadi. The corresponding variational problem leads to a coupled system which is written in terms of the mechanical extensibility, the temperature, and the microtemperatures. An existence and uniqueness result is recalled. Then, we will focus on the numerical approximation of this problem. First, fully discrete approximations are introduced by using the finite element method for the spatial approximation and the implicit Euler scheme to discretize the time derivatives. Second, a discrete stability property is obtained, and an a priori error analysis is performed, from which the linear convergence is derived under adequate additional regularity conditions. Finally, some numerical simulations are presented in order to show the accuracy of the approximations and the behavior of the discrete energy under extensibility and microtemperatures effects.

In this work, experimental tests and numerical simulations are carried out to investigate the buckling behavior and failure modes of auxetic cellular structures and sandwich panels with auxetic cores. Different Poisson's ratios and densities are considered to evaluate the impact of these parameters on the deformation mechanisms under uniaxial compression loading. The numerical analysis is performed using the Riks method, while considering geometric nonlinearity and elastoplastic behavior. The results indicate that negative Poisson's ratio and structure density have a significant influence on the buckling critical stress and the failure mechanisms of cellular structures. Although the inverted honeycomb and the double arrowhead with different Poisson's ratios exhibit similar load capacity, facesheet failure is more pronounced with the conventional inverted honeycomb. This result can be attributed to the dominant effect of the facesheet on the load evolution. The effects of the cell-wall thickness and the facesheet thickness on the buckling load are also discussed based on the finite element model.

The environment, energy, and water are the three essential pillars of sustainable development. In light of the freshwater scarcity faced by numerous countries, desalination emerges as a practical solution. As a result, countries are increasingly establishing desalination facilities along their coastlines. However, these initiatives are energy-intensive, and their chosen locations may not be optimal for harnessing renewable energy resources. With a daily output capacity of 50,000 m³, the recently operational seawater desalination plant in Djerba, Tunisia, accounts for 13.6% of the region's total electrical energy consumption. In this study, we have considered both the specific and the overall desalination consumption to find the optimal architecture and assess the reliability of the hybrid energy generator supplying the unit. The economic optimization has been performed using hybrid optimization of multiple energy resources, and the dynamic study of the complete system has been achieved using the transient system simulation tool environment. On- and off-grid scenarios using various hybrid power system combinations with and without batteries were proposed and examined. Results showed that the optimum case consists of on-grid 60.513 MWp solar panels and 13.64 MW wind turbines with battery storage. The water produced by the most cost-effective strategy with regard to environmental protection for a 25-year project life cycle costs 0.414 $/m³ against 0.585$/m³ for current consumption. This significant reduction in water production costs makes desalination more affordable and accessible. The dynamic behavior of the optimal architecture is designed by considering the real meteorological data of Djerba Island. In terms of productivity, the maximum photovoltaic and wind energy production reached 11.31 GWh in July and 0.51 GWh in April, respectively. The findings demonstrate the technical and economic feasibility of powering large-scale desalination plants with hybrid renewable energy systems, reducing their environmental impact and energy costs. The optimal system proposed in this study can serve as a model for future desalination projects in Tunisia and other water-scarce regions.

This paper presents the results of a numerical investigation by design of experiments of the thermal management of a symmetrical rectangular heat sink for LED lighting placed in a cavity with asymmetrical conditions at its opening. Our mathematical model is validated by an experiment we carried out for an LED placed in a cavity. According to the proposed design of experiments (2⁴ factorial designs), we analyzed, by simulation modeling using COMSOL Multiphysics®, the influence of the different controllable parameters (the position A and width C of the openings, the inlet air velocity B, and the cavity height D) on the evolution of the junction temperature in order to optimize the thermal management of the proposed LED lamp. Using Minitab® manipulation software, a Pareto analysis and an analysis of variance (ANOVA) were carried out, and mathematical models were deduced to estimate the optimal junction temperature and the convective heat transfer coefficient of the proposed radiator and the surrounding air as a function of the controlled parameters. It was found that the position of the opening is the most influential factor on the junction temperature, with a contribution of 93.46%, followed by the factors velocity and width of the opening, with low contributions (3.22% and 1.24%). We also observe that the height of the cavity and the interactions (A × C, A × D, B × C, B × D, C × D) have no significant influence on the junction temperature.

In this work, we analyze numerically, using Comsol Multiphysics, the influence of four parameters (the power of the lamp, the ambient temperature, the angle of inclination of the lamp and the number of holes in the lamp cavity) on the evolution of the junction temperature of a LED lamp placed in a multi-hole cavity using a fractional factorial plan. Taking into account the results obtained, we optimize our model using the Minitab manipulation software. Thus, a Pareto analysis (ANOVA) is carried out and a mathematical model is deduced to estimate the junction temperature of the LED lamp as function of the controlled parameters. The different influencing factors and especially the relative amplitude of their effect on the temperature of the LED chip could thus be calculated and demonstrated. If the electric power supply of the LED remains the first factor of impact on the temperature, the other parameters as well as the number of holes, the angle of inclination or the ambient temperature could thus be prioritized in order of influence. Then an improved model is provided, and its limit with regard to the cavity's condensation detection was examined showing that the risk of water condensation inside the cavity is only detected in the case where the lamp is exposed in an extremely humid area.

The precipitation technique was used to prepare calcium hydroxyapatite pectin (CaHAp‐Pec) and calcium hydroxyapatite xanthan (CaHAp‐Xan) hybrid materials. Chemical analysis, XRD, Fourier transform infrared spectroscopy, specific surface area, TGA and SEM were used to analyze the materials and the organic–inorganic interfaces. XRD and SEM investigations demonstrated that the presence of the biopolymer had an impact on both the structural and morphological properties as well as the crystallinity. The PO4³⁻ vibration modes are visible in the IR spectra, and new vibration modes mostly associated with Xan and Pec are observed at 1594, 2878 and 3246 cm⁻¹. The specific surface area values were reduced after the chemical functionalization of CaHAp with pectin and xanthan gum. The ability of the three materials CaHAp, CaHAp‐Pec and CaHAp‐Xan to sorb methylene blue from aqueous solutions was assessed. The adsorption kinetics results best fitted the pseudo‐second‐order model. The isotherm data agreed well with the Freundlich model. The adsorption capacity values of porous composites CaHAp‐Xan 5%, CaHAp‐Pec 10% and CaHAp reached 277, 243 and 144 mg g⁻¹, respectively. The non‐spontaneous and exothermic nature of the adsorption was demonstrated by the thermodynamic parameters (ΔG⁰, ΔH⁰ and ΔS⁰). Adsorption results confirmed that CaHAp‐Xan could be used as an effective adsorbent of cationic dyes from water. © 2024 Society of Chemical Industry.

Consumer Internet of Things (CIoT) has revolutionised agriculture by integrating intelligent computing, artificial intelligence and big data technologies in crop monitoring. This paper explores the application of intelligent computing and deep learning methodologies in crop monitoring within the CIoT framework. In CIoT‐based crop monitoring, a vision sensor collects real‐time data from crop leaf images. The image dataset is processed using state‐of‐the‐art deep learning models and intelligent computing algorithms. This integration enables the early detection of crop diseases by leveraging computer vision and deep learning. Intelligent computing systems provide accurate disease classification, real‐time alerts, and actionable recommendations for optimised crop management practises. This advanced system empowers farmers to make data‐driven decisions, such as irrigation optimization, targeted pesticide application and nutrient supplementation, to maximise crop productivity and minimise losses. A benchmark dataset of leaf images is used, and a deep learning based model is presented for classifying healthy and diseased leaves. Experimental results demonstrate an accuracy rate of 0.98, with detailed validation, including dataset size and model parameters. Key benefits of intelligent computing in CIoT‐based crop monitoring include enhanced resource efficiency, reduced environmental impact, and improved sustainability. The paper also addresses the challenges of implementing AI and big data technologies, such as data privacy, security, interoperability and resource management in agricultural settings.

This paper investigates the feasibility of non- battery energy storage systems for isolated street lighting, focusing on mechanical storage technologies such as gravity storage, compressed air energy storage, and flywheels. As the global shift toward renewable energy accelerates, the challenge of intermittency in sources like solar and wind becomes increasingly significant. Traditional batteries, while widely used, present limitations in cost, lifespan, and environmental impact. Mechanical storage systems offer promising alternatives, with potential for greater sustainability and efficiency. Through a detailed analysis and comparison of investment costs, this study evaluates the practicality and effectiveness of these non-battery solutions in providing reliable energy storage for a sustainable future.