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1st International Conference on Emerging Electrical Energy, Electronics and Computing Technologies 2019, ICE4CT 2019

作者： Aati, S. Nejim, S. Automatic Control and Marine Robotics Research Unit Naval Academy of Tunisia 7050 Menzel Bourguiba Tunisia

Nowadays, Computational Fluid Dynamic (CFD) analysis is one of the most affordable techniques to determine the aerodynamic characteristics of an aircraft. It allows a development of advanced flight controllers. However, the accuracy of this technique depends on the input parameters such as the solid model. This paper describes a methodology to estimate aerodynamic derivatives of a Cessna 182 aircraft based on solid model established by using photogrammetry technique. 312 images have been taken using Canon D750 camera with a 24 mm lens. A dense point cloud of the aircraft was generated using MicMac photogrammetry software. Then, the aircraft 3D-geometry was extracted in order to create the CAD model. Afterwards, parameters such as lift and drag coefficients were estimated at different angles of attack using Ansys Fluent software. The simulation results show that the lift and drag increase up to stall angle, then the lift starts to decrease. These results matches the theoretical ones. © Published under licence by IOP Publishing Ltd.

关键词： 3D modeling

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COMPARATIVE STUDY OF PHOTOGRAMMETRY SOFTWARE IN INDUSTRIAL FIELD

Revue Francaise de Photogrammetrie et de Teledetection

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Revue Francaise de Photogrammetrie et de Teledetection 2020年第221期1卷

作者： Aati, Saif Rupnik, Ewelina Nejim, Samir Automatic Control & Marine Robotics Research Unit Naval Academy of Tunisia Menzel Bourguiba7050 Tunisia National School of Geographic Sciences Champs-sur-Marne77420 France LASTIG IGN Univ. Gustave Eiffel France

This paper reports a comparative study between photogrammetry software that are able to automatically process image data sets to generate point clouds in the industrial field. As part of a project conducted in Urbica 3D Laser Scanning Survey Company, four industrial data sets were carried out using the following software solution: PhotoScan, Pix4DMapper Pro, RealityCapture, MicMac, ReCap Photo and ContextCapture. Each data set featured a diverse number of images, resolutions and objects of interest with different levels of industrial complexity. The assessment was based on three main criteria: the accuracy of image orientation, the visual quality and the geometric accuracy of 3D dense point clouds and, the different software features such as the time processing and the output variability. © 2020 Soc. Francaise de Photogrammetrie et de Teledetection. All rights reserved.

关键词： Computer vision

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Identification of aircraft aerodynamic derivatives based on photogrammetry and computational fluid dynamics

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Journal of Physics: Conference Series 2020年第1期1432卷

作者： Aati, S Nejim, S Automatic Control & Marine Robotics Research Unit Naval Academy of Tunisia 7050 Menzel Bourguiba Tunisia.

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Economic scheduling of a hybrid microgrid based on weather forecasts

Economic scheduling of a hybrid microgrid based on weather f...

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2017 International Conference on Advanced Systems and Electric Technologies, IC_ASET 2017

作者： Bouaicha, Hamadi Dallagi, Habib Craparo, Emily Nejim, Samir Automatic Control and Marine Robotics Naval Academy Tunisia Department of Operations Research Naval Postgraduate School United States

ISBN: (纸本)9781509066346

Intermittency of renewable resources represents a major impediment that restricts their integration in microgrids. This paper presents an approach that can contribute to solve this issue by the prediction of near-Term future renewable power production, mainly wind power and photovoltaic power, based on weather forecasts. After knowing the future renewable power production, the electric grid manager needs to find the optimal operating plan in order to efficiently integrate the predicted renewable production and to optimally operate other controllable components of the microgrid such as fuel-based generators, energy storage units and connectors to the commercial electric grid. We formulate this optimization problem as an integer linear program and exercise the model to study a number of practical issues surrounding microgrids. © 2017 IEEE.

关键词： Scheduling

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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