μ-PIV characterization of the flow in a milli-labyrinth-channel used in micro-irrigation | Caractérisation de l'écoulement à l'aide de la µ-PIv dans des canaux en labyrinthe utilisés en micro-irrigation
2014
Al Muhammad, J. | Tomas, Séverine | Ait Mouheb, N. | Amielh, M. | Anselmet, F. | Gestion de l'Eau, Acteurs, Usages (UMR G-EAU) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut de Recherche pour le Développement (IRD [France-Sud]) | Institut de Recherche sur les Phénomènes Hors Equilibre (IRPHE) ; Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS)
[Departement_IRSTEA]Eaux [TR1_IRSTEA]GEUSI<br/>17th International Symposium on Applications of Laser Techniques to Fluid Mechanics, Lisbon, PRT, 07-/07/2014 - 10/07/2014
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Show more [+] Less [-]English. The baffle-fitted labyrinth-channel is largely used in micro-irrigation systems. The existing baffles, which play an important role for generating pressure losses and ensure the flow regulation on the irrigation network, produce vorticities where the velocity is low or zero. These vorticities favor the deposition of particles or other biochemical development causing emitter clogging. Flow topology characterization in this labyrinth-channel must be described to analyze emitter clogging sensibility which drastically reduces its performance. This characterization can be performed experimentally using the micro-particle image velocimetry (μ-PIV) technique. In this study, μ-PIV experiments are performed to visualize the flow in ten-pattern repeating baffles used in micro irrigation emitter. Cross section is 1mm2. Reynolds number varies from 400 to 800. This investigation allows analyzing the flow regime. It helps to fix the baffle number from where the flow is developed. Finally, the μ-PIV and modeling results comparisons are presented. The global objective of this study is to identify and analyze the sensitive areas in order to reduce them thanks to geometry optimization.
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