Publications Scientifiques

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    Damage crack growth detection of composite pipeline using NDT
    (Université M'Hamed Bougara Boumerdes : Faculté de Technologie : Département Génie Mécanique, 2021) Brihmat, Chahira; Lecheb, Samir; Chellil, A.; Safi, B.; Kebir, H.; Mechakra, H.; Tablit, B.
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    A new methodology to predict the sequence of GFRP layers using machine learning and JAYA algorithm
    (Elsevier, 2023) Fahem, Noureddine; Belaidi, Idir; Oulad Brahim, Abdelmoumin; Capozucca, Roberto; Thanh, Cuong Le; Khatir, Samir; Abdel Wahab, Magd M.
    In this paper, the best stacking sequence using experimental tests of GFRP composites is investigated. The main objective of this work is to determine the main specification of GFRP composite material, which is represented by its physics-mechanical properties, weight, and cost, before performing a series of experimental tests based on various stacking sequences. Our methodology is divided into three stages. The first stage is characterized by extracting the bending data from mechanical tests of some GFRP composites. In the second stage, the validated numerical model is used to simulate numerous cases of stacking sequences. In the last stage, the extracted data is used to determine the parameters for different stacking sequences using an inverse technique based on ANN and JAYA algorithm. The results provide a good prediction of parameters as well as a good orientation to make decisions on the best GFRP stacking sequence to be used, according to the required specifications of the manufacturer.
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    Sensitivity analysis of the gtn damage parameters at different temperature for dynamic fracture propagation in x70 pipeline steel using neural network
    (Gruppo Italiano Frattura, 2021) Abdelmoumin Ouladbrahim, Abdelmoumin; Belaidi, Idir; Khatir, Samir; Magagnini, Erica; Capozucca, Roberto; Wahab, Magd Abdel
    In this paper, the initial and maximum load was studied using the Finite Element Modeling (FEM) analysis during impact testing (CVN) of pipeline X70 steel. The Gurson-Tvergaard-Needleman (GTN) constitutive model has been used to simulate the growth of voids during deformation of pipeline steel at different temperatures. FEM simulations results used to study the sensitivity of the initial and maximum load with GTN parameters values proposed and the variation of temperatures. Finally, the applied artificial neural network (ANN) is used to predict the initial and maximum load for a given set of damage parameters X70 steel at different temperatures, based on the results obtained, the neural network is able to provide a satisfactory approximation of the load initiation and load maximum in impact testing of X70 Steel
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    Dynamic eccentricity fault diagnosis in induction motors using finite element method and experimental tests
    (Inder Science Online, 2017) Bouzida, Ahcene; Abdelli, Radia; Touhami, Omar; Aibeche, Abderrazak
    This paper presents the dynamic eccentricity (DE) in the squirrel cage induction machine obtained by the simulation using finite element method (FEM) and the experimental tests. Motor current signature analysis (MCSA) through the power spectral density (PSD) is used to monitor the low frequency components related to the rotor faults. In order to generalise the study, a comparison was performed between faulty machines and healthy, under different load conditions. The experimental tests show the encountered difficulties in the detection of the dynamic eccentricity under various load conditions because the spectral representation shows the existence of low frequency components for the healthy case, which are superimposed with the indicator components. These low frequency components offer an alternative way to the monitoring of eccentricity air-gap when the load is balanced
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    Dynamic eccentricity fault diagnosis in induction motors using finite element method and experimental tests
    (Inderscience, 2017) Bouzida, Ahcene; Abdelli, Radia; Touhami, Omar; Aibeche, Abderrazak