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Lakhdar Bouarbi,Bouabdellah Abed,Mohamed Bouzit 한국풍공학회 2016 Wind and Structures, An International Journal (WAS Vol.23 No.6
The objective of this study is to investigate numerically the effect of building roof shaps on wind flow and pollutant dispersion in a street canyon with one row of trees of pore volume, Pvol = 96%. A three-dimensional computational fluid dynamics (CFD) model is used to evaluate air flow and pollutant dispersion within an urban street canyon using Reynolds-averaged Navier–Stokes (RANS) equations and the Explicit Algebraic Reynolds Stress Models (EARSM) based on k-e turbulence model to close the equation system. The numerical model is performed with ANSYS-CFX code. Vehicle emissions were simulated as double line sources along the street. The numerical model was validated by the wind tunnel experiment results. Having established this, the wind flow and pollutant dispersion in urban street canyons (with six roof shapes buildings) are simulated. The numerical simulation results agree reasonably with the wind tunnel data. The results obtained in this work, indicate that the flow in 3D domain is more complicated; this complexity is increased with the presence of trees and variability of the roof shapes. The results also indicated that the largest pollutant concentration level for two walls (leeward and windward wall) is observed with the upwind wedge-shaped roof. But the smallest pollutant concentration level is observed with the dome roof-shaped.
Bouarbi, Lakhdar,Abed, Bouabdellah,Bouzit, Mohamed Techno-Press 2016 Wind and Structures, An International Journal (WAS Vol.23 No.6
The objective of this study is to investigate numerically the effect of building roof shaps on wind flow and pollutant dispersion in a street canyon with one row of trees of pore volume, $P_{vol}=96%$. A three-dimensional computational fluid dynamics (CFD) model is used to evaluate air flow and pollutant dispersion within an urban street canyon using Reynolds-averaged Navier-Stokes (RANS) equations and the Explicit Algebraic Reynolds Stress Models (EARSM) based on k-${\varepsilon}$ turbulence model to close the equation system. The numerical model is performed with ANSYS-CFX code. Vehicle emissions were simulated as double line sources along the street. The numerical model was validated by the wind tunnel experiment results. Having established this, the wind flow and pollutant dispersion in urban street canyons (with six roof shapes buildings) are simulated. The numerical simulation results agree reasonably with the wind tunnel data. The results obtained in this work, indicate that the flow in 3D domain is more complicated; this complexity is increased with the presence of trees and variability of the roof shapes. The results also indicated that the largest pollutant concentration level for two walls (leeward and windward wall) is observed with the upwind wedge-shaped roof. But the smallest pollutant concentration level is observed with the dome roof-shaped.
Yissam Lakhdar,El Hassan Sbai 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.11
The estimation of probability density function (pdf) by the nonparametric kernel methods requires a reliable estimate of the bandwidth. There have been several studies on how to efficiently estimate this parameter. In this work, we propose a new optimization method of the smoothing parameter of the variable kernel estimator (VKE) based on the statistical properties of the probability distributions of random variables. In this setting, we show how to use the maximum entropy principle for estimating the smoothing parameter. The optimized estimator is after used in building the Bayesian classifier. In the same setting, the estimated probability density function is called optimal in the sense of having a minimum error rate of classifying data. Finally, a practical implementation with the aid of a dataset of DNA microarray is used to illustrate the behavior of the optimization technique.
Yissam Lakhdar,El Hassan Sbai 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.3
In this work, we focus on nonparametric kernel methods for estimating the probability density function (pdf). The convergence of a kernel estimator depends crucially on the choice of the smoothing parameter. We present in this paper, a new method for optimizing the bandwidth of an estimator of the probability density function: the adaptive kernel estimator. This optimized estimator is used to construct the Bayes classifier. In this sense, we have proposed a new approach to optimize the pdf based on the statistical properties of the probability distributions of random variables. We adopt the maximum entropy principle (MEP) in order to determine the optimal value of the smoothing parameter used in the estimator. In the proposed criterion, the estimated probability density function is called optimal in the sense of having a minimum error rate of classifying data. Finally, we illustrate the robustness of our optimization process of the kernel estimation methods by using a set of DNA microarray data showing that our approach effectively improves the performance of the classification process.
Rachdi, Lakhdar Tannech,Amri, Besma,Chettaoui, Chirine Department of Mathematics 2016 Kyungpook mathematical journal Vol.56 No.1
We study the Gauss and Poisson semigroups connected with the Riemann-Liouville operator defined on the half plane. Next, we establish a principle of maximum for the singular partial differential operator $${\Delta}_{\alpha}={\frac{{\partial}^2}{{\partial}r^2}+{\frac{2{\alpha}+1}{r}{\frac{\partial}{{\partial}r}}+{\frac{{\partial}^2}{{\partial}x^2}}+{\frac{{\partial}^2}{{\partial}t^2}}};\;(r,x,t){\in}]0,+{\infty}[{\times}{\mathbb{R}}{\times}]0,+{\infty}[$$. Later, we define the Littlewood-Paley g-function and using the principle of maximum, we prove that for every $p{\in}]1,+{\infty}[$, there exists a positive constant $C_p$ such that for every $f{\in}L^p(d{\nu}_{\alpha})$, $${\frac{1}{C_p}}{\parallel}f{\parallel}_{p,{\nu}_{\alpha}}{\leqslant}{\parallel}g(f){\parallel}_{p,{\nu}_{\alpha}}{\leqslant}C_p{\parallel}f{\parallel}_{p,{\nu}_{\alpha}}$$.
M. Haj Lakhdar,B. Ouni,R. Boughalmi,T. Larbi,A. Boukhachem,A. Colantoni,K. Boubaker,M. Amlouk 한국물리학회 2014 Current Applied Physics Vol.14 No.8
Antimonite (Sb2S3) thin films have been synthesized through an annealing process in sulfur vapors at 300 C of Sb thermal evaporated films. Deposited films have been characterized by X-ray diffraction, scanning electron microscopy and UVeviseNIR spectroscopy. X-ray diagrams of these films have confirms that they were well crystallized in orthorhombic structure and some parameters such as the lattice parameter, crystallite size, microstrain and degree of preferred orientation have been reported and correlated with the effect of crystallite size. Optical properties of Sb2S3 films have been characterized by solid-state UVevisible absorption spectroscopy, and the band gap Eg was between 1.75 and 2.23 eV. Moreover, additional opto-thermal investigation and analyses within the framework of the Lattice Compatibility Theory provided plausible explanation for thickness-dependent incorporation of sulfur element inside antimony elaborated matrices.
Analysis of cutting forces and roughness during hard turning of bearing steel
Abderrahim Bouziane,Lakhdar Boulanouar,Mohamed Walid Azizi,Ouahid Keblouti,Salim Belhadi 국제구조공학회 2018 Structural Engineering and Mechanics, An Int'l Jou Vol.66 No.3
An experimental study has been carried out to analyze the effect of cutting parameters (cutting speed, feed and depth of cut) and tool nose radius on the surface roughness and the cutting force components during hard turning of the AISI 52100 (50 HRC) steel with a ceramic cutting tool. The tests have been conducted according to the methodology of planning experiments, based on an orthogonal plan of Taguchi (L27). By using the response surface methodology (RSM), the components of the cutting force and the roughness of the machined surface were modeled and the effects of the input parameters were analyzed statistically by ANOVA and RSM. The results show that the feed (f), the tool nose radius (r), the cutting speed (Vc), the interaction between feed and tool nose radius (f × r) as well as that of the quadratic effect (f2) all have significant effects on the surface roughness (Ra). The feed is the most influencing factor with a contribution of 47.31%. The components of the cutting force were strongly influenced by the depth of cut, followed by the advance with a lower degree. By comparing the experimental values with those predicted by the models of the cutting force components and the surface roughness, it appears that they are in very good correlation.
Ouahid Keblouti,Lakhdar Boulanouar,Mohamed Walid Azizi,Mohamed Athmane Yallese 국제구조공학회 2017 Structural Engineering and Mechanics, An Int'l Jou Vol.61 No.4
In the present paper, the effects of cutting parameters and coating material on the performances of cutting tools in turning of AISI 52100 steel are discussed experimentally. A comparative study was carried out between uncoated and coated (with TiCN-TiN coating layer) cermet tools. The substrate composition and the geometry of the inserts compared were the same. A mathematical model was developed based on the Response Surface Methodology (RSM). ANOVA method was used to quantify the effect of cutting parameters on the machining surface quality and the cutting forces. The results show that feed rate has the most effect on surface quality. However, cutting depth has the significant effect on the cutting force components. The effect of coating layers on the surface quality was also studied. A lower surface roughness was observed when using PVD (TiCN-TiN) coated insert. A second order regression model was developed and a good accuracy was obtained with correlation coefficients in the range of 95% to 97%.
Magnetization Dynamics Modeling in a Like Iron-Silicon Thin Film by the Micromagnetic Approach
Messaoud Boufligha,Lakhdar Bessissa,Djillali Mahi 한국자기학회 2023 Journal of Magnetics Vol.28 No.3
Iron-silicon thin films used as a single layer or in sandwich structures are currently regarded as a promising candidate in high magnetic sensors. A detailed understanding of magnetization dynamics in such thin films is of great interest. In this work, we only focused on modeling the magnetization reversal. Numerical solution to the nonlinear Landau-Lifshitz-Gilbert (LLG) equation can be used to conduct the study. With the help of our developed Matlab code, the simulations were carried out. External field strength, damping parameter and temperature all have an impact on the speed of the magnetization reversal. The validation of our computations is achieved via a separate simulation. It relates to the solution of the standard problem proposed by the micromagnetic Modeling Activity G roup (μMAG ). T he r esults are in agreement with the ones presented in the National Institute of Standards and Technology (NIST) website.