Publications Internationales
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Item Performance of Earth Blocks Based on Recycled Dam Sediment and Reinforced with Alfa Fibers : Experimental Study(Taylor and Francis, 2025) Gueffaf, Nezha; Rabehi, Bahia; Boumaaza, Messaouda; Boumchedda, Khaled; Belaadi, Ahmed; M. S. Abdullah, Mahmood; Klimkina, Iryna; A. al-Lohedan, Hamad; Al-Khawlani, Amar; Chetbani, YazidRiver and dam dredged sediments are regarded as waste. Waste sediment disposal involves financial resources and raises issues regarding the environment. Reusing dredged sediments to make building materials like adobe bricks can offer an alternative way to handle and value this waste. Compressed earth blocks (CEB) are environmentally friendly building materials made from clay soil or sediments dam with fibers. Natural fibers addition improves mechanical and thermal characteristics of adobe bricks. The goal of this study was to use Alfa fibers (AF) from Algeria to create adobe bricks from the sediments of the Koudiat Acerdoune dam. This study presents an experimental study of earth blocks stabilized with 10% cement and reinforced with AF fibers at different volume fraction dosages (0.75%, 1.5%, and 2.5%). The new composite of these sediments’ capillary absorption, shrinkage, compressive strength, flexural strength, and thermal conductivity was examined. With a flexural strength of 2.30 MPa and a compressive strength of 8.12 MPa for 2.5% AFs, as well as a decrease in thermal conductivity, the fiber/cement formulations demonstrated the best mechanical performance, according to the results of the analysisItem Effects of different thermal conductivity models and Ψ sphericity on mixed convection for hybrid nanofluids(Elsevier, 2025) Moussi S.; Abdellahoum C.; Mataoui A.; Oztop H.F.This work focuses on the combined effects of different thermal conductivity formulas for hybrid nanoparticles and the sphericity of these nanoparticles on the thermal behavior of a laminar flow of hybrid nanofluids in mixed convection through a partially heated pipe. The governing equations are solved by the finite volume method and using a structured and non-uniform mesh. This method used allows the behavior of nanofluids, which are complex mixtures of base fluid and nanoparticles, to be modeled. Simulations can take into account aspects such as the Brownian motion of particles and interactions between particles and fluid, thus improving the understanding of heat transfer phenomena. A percentage selection was made for a wide range of copper (5 %, 10 %, 15 %, 25 %, 40 %, 50 %) and three nanoparticle volume fractions (ϕ = 0.5 %, 2 %, 5 %). It was found that the effect of Cu is notable in the upper part of the section, where free convection is dominant in the presence of forced convective heat transfer due to the flow. We can also say that the percentage of copper and aluminum in nanofluids is a variable parameter and adjusted according to the application. There is no single value, but rather a range of concentrations that allows the desired performance to be achieved. A comparison between the numerical results and the experimental measurements available in the literature is carried out in order to validate the chosen numerical procedure. The Brownian model is associated with higher thermal conductivity, which means a greater ability to transfer heat. The Maxwell and Hamilton models show heat transfer characteristics very close to each other, which makes them less efficient than the Brownian model. This observation is crucial for choosing the most suitable model for an application where efficient heat transfer is sought, indicating that the processes describing the motion of particles in the Brownian model are the most efficient for moving thermal energy. Moreover, there is an increase in the average coefficients hup and hlow as the volume fraction of the nanoparticles in the fluid increases, for all values of the shape factor n1 of the alumina oxide particles, which represents 90% of the total volume fraction ϕ.Furthermore, the sphericity of nanoparticles affects the thermal properties of nanofluids by altering the interaction between the particles and the base fluid, as well as the particle arrangement. More spherical particles tend to maintain greater fluidity, reducing friction and aggregation, which can improve the thermal conductivity and stability of the nanofluid. The increase in thermal conductivity, one of the key properties of nanofluids, is directly influenced by this morphologyItem Optimizing Foam Concrete Performance Using Mixed Foaming Method: Impact of Mixing Speed, Mixing Duration, And Foam Dosage(South Florida Journal of Development, 2024) Galoul, Riadh; Boumchedda, Khaled; Mebtouche, FaroukFoamed concrete has gained significant attention, especially in the field of thermal insulation and acoustic insulation. However, all production methods are based on the pre-foaming method, while the mixed foaming method is an infrequent approach that should be considered and could be challenging. For this reason, this paper attempt to highlight this method and valuate it on par with the pre-foaming method in the production of foamed concrete, both in terms of structure and performance. These performances are directly dependent on the pore structure of this material (pore size, porosity rate, and pore distribution). Therefore, a process has been developed for sample preparation to achieve a final product with a well-controlled size and distribution of porosity, meeting the desired performance criteria. This process involves varying the following parameters: mixing speed (from 400 to 1000 rpm), mixing time (from 2 to 12 minutes), and the dosage of foaming agent (from 0.05 to 0.2%). The effect of mixing speed, mixing duration and the dosage of the foaming agent on the generated foam rate, density, structure at the millimeter scale, structure at the micrometer scale, and thermal conductivity was demonstrated. The obtained results show that with a generated foam rate extending to 79%, a density reaching 428 kg/m3, and a thermal conductivity achieving 0.181 w/k.m, the mixed foaming method becomes an important and competitive approach to the pre- foaming method in the production of foamed concrete.Item Sustainable composite materials with date palm rachis fibers for enhanced insulation and structural integrity(Institute of Physics, 2024) Ferhat, Maroua; Djemai, Hocine; Guettaf Temam, Elhachmi; Labed, Adnane; Lahag, Lemya; Sid Amer, YoucefThis investigation focuses on the development and characterization of sustainable composite materials for insulation and structural components in the automotive and shipbuilding industries, by incorporating date palm Rachis fibers into an epoxy matrix. Thus, we evaluated the effect of the weight ratio (ranging from 0 to 15 wt%) of Rachis fibers (0.315 mm) on the mechanical, physical, surface morphology, thermal properties, and water absorption. It turns out according to the study that, the XRD pattern revealed the amorphous nature of the composite. This new material can be used as composite material itself or as a skin of a sandwich composite material. The Epoxy-Rachis (ER) composite materials exhibited a low thermal conductivity of 0.21 W/ (m.K) and a low thermal diffusivity of 0.17 mm2 s−1 presenting high thermal insulation and construction properties. The SEM images showed that increasing Rachis fiber concentration produces a heterogeneous bio-composite material. The resulting composition showcases ductile fracture behavior with a flexural modulus (Ef) of 3.21 GPa and a bending strength (σ) of 9.28 MPa. These attributes underline the suitability of this composite for applications requiring efficient thermal insulation and robust construction properties, while simultaneously contributing to environmental sustainability and environmental benefits.Item Predicting thermal conductivity of carbon dioxide using group of data-driven models(Elsevier, 2020) Nait Amar, Menad; AshkanJahanbani, Ghahfarokhi; Zeraibi, NoureddineThermal conductivity of carbon dioxide (CO2) is a vital thermophysical parameter that significantly affects the heat transfer modeling related to CO2 transportation, pipelines design and associated process industries. The current study lays emphasis on implementing powerful soft computing approaches to develop novel paradigms for estimation of CO2 thermal conductivity. To achieve this, a massive database including 5893 experimental datapoints was acquired from the experimental investigations. The collected data, covering pressure values from 0.097 to 209.763 MPa and temperature between 217.931 and 961.05 K, were employed for establishing various models based on multilayer perceptron (MLP) optimized by different back-propagation algorithms, and radial basis function neural network (RBFNN) coupled with particle swarm optimization (PSO). Then, the two best found models were linked under two committee machine intelligent systems (CMIS) using weighted averaging and group method of data handling (GMDH). The obtained results showed that CMIS-GMDH is the most accurate paradigm with an overall AARD% and R2 values of 0.8379% and 0.9997, respectively. In addition, CMIS-GMDH outperforms the best prior explicit models. Finally, the leverage technique confirmed the validity of the model and more than 96% of the data are within its applicability realmItem Experimental thermal characterization of bio-based materials (Aleppo Pine wood, cork and their composites) for building insulation(Elsevier, 2016) Limam, Amel; Zerize, Abdellatif; Quenard, Daniel; Sallee, Hebert; Chenak, Abdelkrim