Publications Internationales
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Item Using Machine Learning Algorithms for the Analysis and Modeling of the Rheological Properties of Algerian Crude Oils(Taylor and Francis Ltd., 2024) Souas, Farid; Oulebsir, RafikOur research described in this report investigated the rheological behavior of crude oils from the Tin Fouye Tabankort oil field in Southern Algeria, focusing on their viscosity under varying temperatures (10 °C–50 °C). The results show that the oils exhibited non-Newtonian shear-thinning behavior at low shear rates, with the viscosity decreasing as the temperature was increased. At higher shear rates, the Herschel–Bulkley model accurately described the oils’ transition to Newtonian behavior. Machine learning models, including CatBoost, LightGBM, and XGBoost, were trained on the experimental data to predict the viscosity, with CatBoost and XGBoost showing superior performance. We suggest these findings are valuable for improving the efficiency of oil transportation and processing.Item Phase Transition and Atomic Distances Behavior of ZnO Rocksalt Structure under Extended Pressure: a Parallel and Equilibrium MD Computation Yahia Chergui(Preprints, 2023) Chergui, Yahia; Ouatizerga, Abd elaziz; Salah, Essma RedouaneZinc oxide (ZnO) as a semiconductor in its crystalline or amorphous form is still a promised material, especially under isobaric and isothermal ensembles. In this work, Parallel and Equilibrium Molecular Dynamics and DL_POLY_4 software are employed to predict the relationship between the behavior of ZnO chemical bonds and the phase transition literatures, using correlation function g(r) of Zn-Zn, Zn-O, and O-O pairs. Our system is composed of 5832 atoms of ZnO rocksalt structure (2916 atoms of Zn2+ and 2916 atoms of O2-), under the temperature of 300 (K) and the range of pressure 0-400 (GPa). The lengths of ZnO bonds, the standard error, standard deviation, the maximum of g(r), and the percentage of the variation of the bonds are analyzed. The interatomic interactions are modeled by the potential of Buckingham for short-range and Coulomb for long-range interactions. The calculations were run on the RAVEN Supercomputer of Cardiff University (UK). Our data are mostly in the vicinity of available information of bonds lengths; the rest can be deduced from the pressure of phase transition to use it as a new approach of phase transition confirmation. However, the rest of our results are still a prediction because of no results under extended pressure used in this work. These data have huge importance, as it is required to be used in many industrial sectors, geophysics, Medicine, and Pharmacy, especially in nanoscale and materials design.Item Numerical study of temperature and pressure effects of a yield-power law fluid flow on frictional pressure losses for laminar and turbulent regimes(Taylor and Francis, 2024) Messaoud, Nadia; Hadjadj, Ahmed; Ferroudji, HichamThe effective determination of pressure losses depends on accurate knowledge of the drilling fluid rheology. As the fluid circulates deeper around the wellbore, its rheological behavior undergoes significant alterations due to the variations in downhole conditions encountered. The present study investigates the effects of the rheological properties of Yield-power law fluid at various pressures and temperatures on annular pressure losses and velocity profiles. Simulations were performed using Computational Fluid Dynamics to examine the fluid flow in turbulent and laminar regimes. Comparison between numerical, experimental and slot approximation model results showed a good agreement. Results indicated that pressure losses have reduced in both regimes with increasing temperature, at a constant pressure. However the pressure has the opposite effect at a constant temperature. For a drilling fluid flow velocity of 1 m/s, the elevation of temperature from 25 °C to 90 °C, decreases the pressure drop gradient by (31% to 48%) at low and high- pressure conditions respectively. Whereas, the influence of increasing pressure on pressure losses is more apparent at 25 °C. Earlier transition from laminar to turbulent is observed with temperature rise. Therefore, the temperature effect on pressure losses in the turbulent region; is shown for different Generalized Reynolds numbersItem Effect of temperature on the performance of CGS/CIGS tandem solar cell(2023) Elbar, Mourad; Tobbeche, Souad; Chala, Slimane; Saidani, Okba; Kateb, Mohamed Nadjib; Serdouk, Mohamed RedhaThe CGS and CIGS being promising materials for large scale photovoltaic applications, the effect of temperature on the electrical parameters of a CGS/CIGS tandem solar cell has been investigated in this work. The copper gallium diselenide (CGS) and copper indium gallium diselenide (CIGS) structures as topcell and bottom-cell respectively, were numerically simulated under AM1.5G spectral illumination using the two-dimensional device simulator Silvaco-Atlas. The temperature dependency of the solar cell’s characteristics was investigated in the temperature range from 300 to 400 K at intervals of 20 K. The simulation results show the density current (Jsc) slightly increases whereas the open-circuit voltage (Voc) and fill factor (FF), conversion efficiency () decreases with the increase in temperature. The tandem cell operating temperature efficiency was found to be (– 0.34 %/K), which is slightly higher than that of CGS solar cell (– 0.29 %/K), but markedly better than that of CIGS solar cell (– 0.41 %/K)Item Effect of Temperature on the Performance of CGS/CIGS Tandem Solar Cell(Sumy State University, 2023) Elbar, Mourad; Tobbeche, Souad; Chala, Slimane; Saidani, Okba; Kateb, Mohamed Nadjib; Redha Serdouk, MohamedThe CGS and CIGS being promising materials for large scale photovoltaic applications, the effect of temperature on the electrical parameters of a CGS/CIGS tandem solar cell has been investigated in this work. The copper gallium diselenide (CGS) and copper indium gallium diselenide (CIGS) structures as topcell and bottom-cell respectively, were numerically simulated under AM1.5G spectral illumination using the two-dimensional device simulator Silvaco-Atlas. The temperature dependency of the solar cell’s characteristics was investigated in the temperature range from 300 to 400 K at intervals of 20 K. The simulation results show the density current (Jsc) slightly increases whereas the open-circuit voltage (Voc) and fill factor (FF), conversion efficiency (ƞ) decreases with the increase in temperature. The tandem cell operating temperature efficiency was found to be (– 0.34 %/K), which is slightly higher than that of CGS solar cell (– 0.29 %/K), but markedly better than that of CIGS solar cell (– 0.41 %/K).Item Rheological behavior of oil sludge from Algerian refinery storage tanks(Elsevier, 2022) Souas, FaridRheological behavior of oil sludge from Algerian refinery storage tanks Farid Souas a, b, * a LEGHYD Laboratory, Faculty of Civil Engineering, University of Science and Technology Houari Boumediene (USTHB), Bab Ezzouar, Alger, Algeria b Research Unit Materials, Processes and Environment (UR-MPE), Faculty of Engineering Science, University M’Hamed Bougara, Boumerdes, Algeria a r t i c l e i n f o Article history: Received 15 August 2021 Received in revised form 20 December 2021 Accepted 28 January 2022 Available online xxx Keywords: Crude oil Rheology Sludge Storage tank Temperature Viscosity a b s t r a c t The consumption and demand for petroleum are increasing dramatically with the rapid development of industry and energy sector. As a result, petroleum refineries produce the greatest amount of oily sludge formed at the bottom of storage tanks during oil storage operations, which has a severely negative impact on the storage capacity and the operational safety of the storage tank. The present study focuses on the rheology of this complex fluid from Algerian crude oil storage tanks. Rheological measurements were performed at different temperatures under steady shear and dynamic oscillometry using AR-2000 Rheometer. The results obtained show that the sludge exhibits yield-pseudoplastic flow behavior at low shear rates, which is adequately described by the Herschel Bulkley model based on the standard error and correlation coefficient values. However, quasi-Newtonian flow behavior occurs at very high shear rates. The increase in temperature had positive effects on the rheological properties of the sludge, including dynamic viscosity, shear stress, yield stress, complex modulus, elastic modulus and viscous modulus. The dynamic rheology studies have shown that the sludge material behaves more like a solid than a liquid under all experimental conditions studiedItem Behavior of phase transition of ZnO in nanoscale of time a molecular dynamics computation(IOP Publishing, 2021) Chergui, Yahia; Aouaroun, Tahar; Hadley, Mark J; Chemam, Rafik; Ouatizerga, A.The phase transition of Zinc Oxide Wurtzite structure is investigated at the nanoscale of time using Equilibrium time of total energy in isobaric and isothermal ensemble. The calculations ran on the RAVEN supercomputer of Cardiff University employing Molecular Dynamics simulation and DL_POL_4 software, the short and long-range interatomic interactions modeled by Bukingham-Coulomb potential. In this work we used low and high range of pressure and temperature of 0-30 GPa and 40-200 GPa, and 300-500 K and 1500-3000 K respectively. Although no data about confirming phase transition using equilibrium time of total energy as our knowledge, our results are in agreement with the classical method but are still a prediction which needs experimental confirmation. This work has great importance in nanotechnology and many industrial and academic sectorsItem Comparative performance evaluation of four photovoltaic technologies in saharan climates of Algeria: ghardaïa pilot station(Indonesian Journal of Electrical Engineering and Computer Science, 2020) Tadjer, Sid Ahmed; Idir, Abdelhakim; Chekired, FathiaThe aim of this paper is to present an evaluation of the performancerateof four different photovoltaic techniques in the Saharan environment. The purpose of this study is to investigate, analyse, discuss and illustrate the most effective of the different photovoltaic cell technologies (monocrystalline(𝑚−𝑠𝑖), amorphous silicon (𝑎−𝑠𝑖), poly-crystalline silicon (𝑝𝑐−𝑠𝑖)and cadmium telluridethin film(𝐶𝑑𝑇𝑒−𝑇𝐹)) installed in Ghardaia which is located in southern ofAlgeria’s Sahara desert. In order to choose the most suitable technology in the Saharan climate conditions, the energy values produced by the plant were compared to those found by the PVSYST sizing software. The results show that thin-film and amorphous silicon panels produce low illumination, so they are the best choice for the Saharan environment.Item Experimental investigation of the rheological behavior of algerian crude oils from the quagmires(Taylor & Francis, 2019) Souas, Farid; Safri, Abdelhamid; Benmounah, AbdelbakiItem Deep convolutional neural networks for Bearings failure predictionand temperature correlation(JVE International, 2018) Belmiloud, D.; Benkedjouh, T.; Lachi, Mohammed; Laggoun, A.; Dron, J. P.Rolling elements bearings (REBs) is one of the most sensitive components and the common failure unit in mechanical equipment. Bearings failure prognostics, which aims to achieve an effective way to handle the increasing requirements for higher reliability and in the same time reduce unnecessary costs, has been an area of extensive research. The accurate prediction of bearings Remaining Useful Life (RUL) is indispensable for safe and lifetime-optimized operations. To monitor this vital component and planning repair work, a new intelligent method based on Wavelet Packet Decomposition (WPD) and deep learning networks is proposed in this paper. Firstly, features extraction from WPD used as input data. Secondly, these selected features are fed into deep Convolutional Neural Networks (CNNs) to construct the Health Indicator (HI). This study focuses on analysing the relationships such as correlations between the HI and temperature. We develop a solution for the Connectiomics contest dataset of bearings under different operating conditions and severity of defects. The performance of the proposed method is verified by four bearing data sets collected from experimental setup called “PRONOSTIA”. The results show that the health indicator obtains fairly high monotonicity and correlation values and it is beneficial to bearing life prediction. In addition, it is experimentally demonstrated that the proposed method is able to achieve better performance than a traditional neural network based method