Institut Supérieur des Études Technologiques de Gafsa

The paper aims to analyze and optimize the FSWing process of plates in a butt configuration. The ultimate objective is to desensitize the process to both endogenous and exogenous noises, which are lacing the manufacturing process.. To this end, the Robust Design for Products and Processes using the stochastic frontier (RDPP-SF) and the Taguchi-Grey methods are employed, and settings of the process parameters, which yield the best mechanical performances, are sought. The process parameters are the pin rotation speed (x 1 ), feed rate (x 2 ), and plunged surface (x 3 ), whereas the process responses are the longitudinal stress (σ L ), transverse stress (σ T ), longitudinal strain (ε L ), and transverse strain (ε T ) that occur in the FSWed seams. Three replications of an FCCD design are conducted and then statistically analyzed. For the RDPP-SF method, the optimal mechanical properties are σ L = 22.197 MPa, σ T = 22.607 MPa, ε L = 18.33 %, and ε T = 15.83 % and they occur when setting the rotation speed (x 1 ) at 1700 rpm, the feed rate (x 2 ) at 29 mm/min, and the plunged surface (x 3 ) at 478 mm 2 . The optimal values with regard to the Taguchi-Grey method are achieved at, σ L = 23.733 MPa, σ T = 23.886 MPa, ε L = 17.76 %, and ε T = 16.91 % while setting the rotation speed (x 1 ) at 1280 rpm, the feed rate (x 2 ) at 29 mm/min, and the plunged surface (x 3 ) at 478 mm 2 . The discrepancy between the RDPP-SF and the Taguchi-Grey method is partly due to the variance decomposition models, which are employed.

This chapter explores the essential practices for brands and companies to effectively master content marketing in order to attract, engage, and retain their target audiences. It emphasizes the integration of content strategy into the broader communication strategy, focusing on the delivery of relevant and tailored messages. The study first consolidates theoretical knowledge by examining key concepts such as content marketing on social media and the steps involved in developing a digital content strategy. It further identifies various content formats that brands can produce and the mechanisms for sustaining content over time. Additionally, the chapter highlights the role of storytelling, its different forms, and its integration into content strategy, particularly its importance for luxury and premium brands in enhancing brand identity.

The printed electronics sector is experiencing significant growth driven by societal expectations. The use of cellulosic substrates is an excellent strategy that offers interesting research prospects, but also sets challenges in terms of management and recycling of these new wastes to avoid their accumulation. This work investigates the recycling ability of paper-based printed electronics (a simple RFID antenna printed on paper), containing silver particles in the functional ink, using processes already applied in conventional paper and board recycling lines. These operations, commonly used in the papermaking industry, are pulping, screening, centrifugal cleaning, and flotation. The efficiency of each unit operation was evaluated. Mass balances between the inlet and the outlet of each studied operation have been established in order to evaluate the separation efficiency of Ag and cellulosic fibers, the objective being to reuse the fibers to manufacture a recycled paper, and to recover Ag in another fraction for further valorization. The results are encouraging, with more than 70% of silver and over 80% of cellulose fibers recovered, demonstrating a higher recovery efficiency compared to typical recycling methods reported in the literature. Thus, it has been shown that existing processes used in conventional recycling lines can be adapted to efficiently separate functional materials from cellulosic fibers, offering an improvement in both metal and fibers’ recovery.

This study explores a topological optimization approach for an automotive suspension arm made of 1040 (AISI) steel, aiming to reduce mass while maintaining structural integrity. A novel CAD–RSM–AI framework is introduced, combining computer-aided design, response surface modeling, and meta-heuristic optimization into a unified process. The methodology provides a systematic way to address geometric weaknesses and enhance mechanical performance. Beyond the suspension arm case, the approach offers a transferable strategy that can be adopted for the design of other lightweight and reliable components. This work highlights the potential of coupling numerical modeling with metaheuristic algorithms to advance industrial design optimization.

Seedling plasticity in Poaceae, particularly in Stipa tenacissima L., represents a key adaptive mechanism for survival in arid steppes. This plasticity is essential for the species’ persistence and success under harsh environmental conditions. In the present study, we examined the leaf and root morphological traits and plasticity in relation to the seed-source rainfall of Stipa tenacissima (Alfa grass), a key species in the arid and semi-arid environments of the Mediterranean Basin. Populations representing a rainfall range of 100 to 400 mm per year at the seed collection sites were grown in a common garden. Populations differed significantly in TB, leaf traits, and several root traits, with Hassi El Frid showing higher above-ground biomass and leaf architecture, and Sfax populations exhibiting larger root systems. Specific root length (SRL) and leaf traits were positively correlated, while mean root diameter (MRD) decreased with increasing aridity. Plasticity indices revealed high variability among populations, with Sbeitla showing the greatest trait plasticity. Principal component analysis grouped populations according to functional trait expression, explaining 72.7% of total variance. Our results indicate that seedling trait variation is influenced by both local climate and genetic differentiation. Resource allocation patterns support the optimal partitioning theory, with xeric populations favoring root investment and mesic populations favoring leaf development. These findings highlight the adaptive strategies of S. tenacissima seedlings to cope with aridity, providing insights for predicting species responses to climate change and informing conservation of Mediterranean drylands.

The synthesis of cellulose extracted from agricultural waste, specifically almond and fig tree trimmings, and its combination with ZnO nanoparticles to form cellulose/ZnO composites was studied. These adsorbents/photocatalysts were fully characterized, confirming not only the effective deposition of zinc oxide nanoparticles on the cellulose surface but also the improvement in homogeneity and lower agglomeration and size of ZnO particles grown on these fibers (crystallites were 43 ± 12 nm for pristine ZnO and 13–26 nm for composites). The efficacy of these composites was evaluated against methylene blue (MB), methyl orange (MO), and bromophenol blue (BB), this study being the first time that BB removal results have been reported using dual photo-adsorptive cellulosic composites. After 20 min, removals of approximately 45% were achieved for the anionic dyes MO and BB under UV light and up to 65% for MB with either applied radiation, indicating a clear adsorption mechanism for this cationic dye. A reusability study was conducted for the BB removal system, with only a 15–19% loss in BB removal capacity under UV irradiation after the third reuse. These results demonstrated the potential and efficiency of cellulose/ZnO composites as promising photocatalysts for textile wastewater treatment, providing a sustainable and interesting approach to mitigate dye pollution.

The structural, electronic, and magnetic properties of bismuth ferrite (BiFeO3) and Bi2Fe4O9 nanostructures were investigated using Density Functional Theory (DFT) within the Generalized Gradient Approximation (PBE-GGA) plus U approach. The PBE-GGA + U calculations predict band gaps of 2.4 eV for BiFeO3 and 2.3 eV for Bi2Fe4O9, closely aligning with experimental data. The analysis of partial and total density of states reveals strong hybridization between iron 3d and oxygen 2p states, with a significant contribution from Fe 3d orbitals in both structures. Additionally, nanostructure and crystal symmetry are crucial in influencing the magnetic properties of BiFeO3 and Bi2Fe4O9. Our calculations indicate that the antiferromagnetic phase is energetically more favorable than the ferromagnetic phase in both materials.

Green energy production systems have received significant attention for their contributions to environmental conservation and economic progress. This paper focuses on the feasibility of producing electrical energy through a 30 kV grid-connected photovoltaic power system. Connection to the grid leads us to synthesise the static converters: the boost chopper regulates the voltage and performs the MPPT function, three-phase inverter is controlled by the PWM which couples it to the grid. In fact, the initial objective is achieved by utilizing an MPPT plan based on $\mathrm{P} \& \mathrm{O}$ methodology to maximize the PV power that is injected into the grid. By applying PWM control to the power inverter, the second goal can be achieved. The MATLAB-Simulink environment has been used to verify the performance of this control strategy for various static and dynamic power flow regimes. The MATLAB-Simulink environment has been used to verify the performance of this control strategy for various static and dynamic power flow regimes.

Abstract Roller burnishing is being extensively employed for improving surface quality and saving manufacturing cost, while its parameters' optimization, especially the trade-off between surface roughness and power consumption, still faces difficulties. The purpose of this research is to predict and optimize the process on AISI 1045 steel through the RSM approach and a hybrid PSO-ANN model. The results show that the burnishing force (F) has the maximum influence on surface roughness (50.9%), followed by spindle speed (N), while the latter has its maximum influence on power consumption (92.37%). When the F increases, the surface finishes better with increasing power consumption. The PSO-ANN model has high prediction accuracy (R² = 0.9911 for Ra, 0.9987 for Pb) and outperforms the response surface method. MOALO and MOGWO algorithms also produce close optimum parameters, where MOALO promotes power efficiency. The optimal parameters yielded by MOALO are N = 300 rpm, f = 0.11 mm/rev, and F = 129.84 N. These parameters yield a burnishing power of 0.5041kW and roughness of 1.42 µm.