Browsing by Author "Ait Chikh, Mohamed Abdessamad"

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    Coupling of inverse method and cuckoo search algorithm for multiobjective optimization design of an axial flow pump
    (Sage journals, 2019) Abdessamad, Mohamed; Ait Chikh, Mohamed Abdessamad; Belaidi, Idir; Khelladi, Sofiane
    his work describes the application of a multiobjective cuckoo search method for turbomachinery design optimization of an axial pump. Maximization of the total efficiency and minimization of the required net positive suction head of the pump are the two objective functions considered for the optimization problem. The optimization process is carried out on a range of imposed volumetric flow rates, with taking into account at each discretized radius between the hub and tip of the rotor: the profile camber, rotor wall thickness, angular deviation, and the solidity, regarded as geometrical constraints and nominal flow rate as mechanical constraint. Two strategies are proposed in order to solve the problem. In the first one, three forms of mono-objective model with two variables, total efficiency and net positive suction head, are considered. In the second one, a multiobjective model with nondominated sorting scheme is adopted. A comparative evaluation of results obtained from the proposed approach with those of a reference machine and genetic algorithm allowed us to validate the present work
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    Crack identification in plates-type structures using natural frequencies coupled with success-history based adaptive differential evolution algorithm.
    (EBESCO, 2023) Brihmat, Chahira; Amoura, Nasreddine; Lecheb, Samir; Kebir, Hocine; Ait Chikh, Mohamed Abdessamad; Tablit, Bassima
    In this study, a new method for identifying and characterizing straight cracks in plate-like structures is presented. The method combines the finite element method (FEM) using the software Abaqus and the success history-based adaptive differential evolution algorithm (SHADE). The objective of the method is to minimize the mean relative error between the measured experimental frequencies of a plate with an unknown crack identity and the numerical frequencies obtained using the Shade-FEM approach. The crack identity is defined by its length, orientation, and centre coordinates. To validate the effectiveness of the proposed approach, two strategies are applied. In the first strategy, the inverse problem is solved using the natural frequencies of a plate with a known crack identity obtained through modal simulation in Abaqus. In the second strategy, the experimental frequencies of a cracked plate are used. The results of the study demonstrate that the proposed approach achieves promising results with just a population size of 25 and 150 iterations. The outcomes show high accuracy, as indicated by a relative error of the objective function below 0.8%. Overall, the study demonstrates the effectiveness of using the Shade-FEM approach for identifying and characterizing straight cracks in plate-like structures, offering potential applications in various engineering and structural integrity fields.
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    Efficiency of bio- and socio-inspired optimization algorithms for axial turbomachinery design
    (Elsevier, 2017) Ait Chikh, Mohamed Abdessamad; Belaidi, Idir; Khelladi, Sofiane; Paris, José; Deligant, Michael; Bakir, Farid
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    Energy-based USV maritime monitoring using multi-objective evolutionary algorithms
    (Elsevier, 2022) Ouelmokhtar, Hand; Benmoussa, Yahia; Benazzouz, Djamel; Ait Chikh, Mohamed Abdessamad; Lemarchand, Laurent
    This study addresses the monitoring mission problem using an USV equipped with an on-board LiDAR allowing to monitor regions inside its coverage radius. The problem is formulated as a bi-objective coverage path planning with two conflicting objectives : minimization of the consumed energy and maximization of the coverage rate. To solve the problem, we use two popular multi-objective evolutionary algorithms : Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Pareto Archived Evolution Strategy (PAES). First, we compare the efficiency of these two algorithms and show that PAES allows to find solutions allowing to save more energy as compared to those provided by NSGA-II. Then, we propose a new method which improves the performance of evolutionary algorithms when solving covering path planning problems by reducing the chromosome size. We have applied this method on the used algorithms and simulation results shows a significant performance enhancement both PAES and NSGA-II.
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    Mise en place d’une méthodologie de dimensionnement couplée à des méthodes d’optimisation géométrique pour l’analyse et le contrôle des performances des turbomachines axiales compressibles
    (2018) Ait Chikh, Mohamed Abdessamad; Belaidi, Idir(Directeur de thèse)
    Les turbomachines sont omniprésentes dans notre environnement domestique et industriel. Les applications vont de la climatisation à la distribution d’eau et de l’automobile aux moteurs aéronautiques et navals. La conception de ces machines pose un problème complexe de design, dont la résolution nécessite une expérience approfondie, en raison d’un grand nombre de paramètres de conception à considérer, toujours plus grand que le nombre d’équations possibles. Le développement actuel de nouveaux outils numériques et de méthodes d’optimisation performantes et pertinentes, ont permis de rendre plus flexible et plus rapide la procédure de résolution. Cette dernière est basée sur le paramétrage de la géométrie, un modèle pour l’évaluation de la performance d’une géométrie donnée, et la définition d’une fonction objectif et des contraintes pour comparer des solutions. Dans ce présent travail, nous mettons en exergue la nécessité de mettre en oeuvre une approche d’optimisation du design, dans le cadre de la conception des turbomachines axiales de compression à fluide incompressible (pompe et ventilateur). L’approche proposée est basée sur le design inverse analysé par la méthode directe, et son couplage avec des méthodes d’optimisation de type bio- et socio-inspiré dans leur version mono- et multi-objectif, à l’exemple des algorithmes génétiques (GA), de l’optimisation par essaime particulaire (PSO), de la recherche de coucou (CS) et de l’optimisation basée sur l’enseignement et l’apprentissage (TLBO). Différentes formulations d’optimisation sont proposées et adaptées à la résolution du problème du design des turbomachines considérées. Chaque formulation représente une approche, basée sur des nouvelles fonctions objectif, avec prise en compte d’un nombre de contraintes géométriques et mécaniques le plus élevé possible. Enfin, les résultats du design optimal des machines considérées ont été validés par simulation numérique basée sur la dynamique des fluides numérique (CFD), et dans certains cas, par comparaison avec des approches de design relevées de la littérature consultée
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    Performance Prediction of Cross-Flow fans Using Loss Correlations
    (2022) Himeur, Rania Majda; Khelladi, S.; Belaidi, I.; Ait Chikh, Mohamed Abdessamad
    Cross-flow fans (CFF) are double-stage cooling machines that have been invented in 1892 by Paul Mortier. Despite their early appearance, the CFFs did not get the same success as the axial or centrifugal fans, due to their weak efficiency and longwise form. However, they proved their usefulness in multiple domains such as air conditioners, and aircraft wings. The literature shows that many researchers attempted to predict their performances. Nevertheless, prior studies were limited to a few CFF designs, and the approaches could not be generalized. The main purpose of the present paper is to determine the characteristic curves of the pressure of the Eck CFF. It is a one-dimensional study that investigates several approaches of loss models inspired by those occurring in pumps, axial fans, or compressors, by using velocity triangles of the mean streamline. We will also reveal some parameters and hypotheses not mentioned in the literature. A basic apparatus was employed to collect the experimental results. The setup consists of a cross-flow fan of 24 forward curved blades and a surrounding casing. The Euler head and the pressure rise were extracted and compared with the theoretical results. The pressure coefficients obtained with the loss model corroborate the experience with good accuracy. Hence, the proposed methodology presents a good (first) approach to analyzing the performances of CFFs
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    Towards an accurate aerodynamic performance analysis methodology of Cross-Flow fans
    (MDPI, 2022) Himeur, Rania Majda; Khelladi, Sofiane; Ait Chikh, Mohamed Abdessamad; Vanaei, Hamid Reza; Belaidi, Idir; Bakir, Farid
    Cross-flow fans (CFFs) have become increasingly popular in recent years. This is due to their use in several domains such as air conditioning and aircraft propulsion. They also show their utility in the ventilation system of hybrid electric cars. Their high efficiency and performance significantly rely on the design parameters. Up to now, there is no general approach that predicts the CFFs’ performance. This work describes a new methodology that helps deduce the performance of CFFs in turbomachinery, using both analytical modeling and experimental data. Two different loss models are detailed and compared to determine the performance–pressure curves of this type of fan. The efficiency evaluation is achieved by realizing a multidisciplinary study, computational fluid dynamics (CFD) simulations, and an optimization algorithm combined to explore the internal flow field and obtain additional information about the eccentric vortex, to finally obtain the ultimate formulation of the Eck/Laing CFF efficiency, which is validated by the experimental results with good agreement. This approach can be an efficient tool to speed up the cross-flow fans’ design cycle and to predict their global performance