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     <dc:title xml:lang="en">Lagrangian coherent motions to track particle trajectories in turbulent flows</dc:title>
     <dcterms:alternative xml:lang="fr">Mouvements cohérents lagrangiens pour suivre les trajectoires des particules dans les écoulements turbulents</dcterms:alternative>
     <dc:subject xml:lang="fr">Vélocimétrie par suivi de particules</dc:subject><dc:subject xml:lang="fr">structures cohérentes lagrangiennes</dc:subject><dc:subject xml:lang="fr">mouvements cohérents lagrangiens</dc:subject>
     <dc:subject xml:lang="en">Particle tracking velocimetry</dc:subject><dc:subject xml:lang="en">Lagrangian coherent structures</dc:subject><dc:subject xml:lang="en">Coherent motions</dc:subject>
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     <dcterms:abstract xml:lang="fr">Dans cette thèse, nous avons étudié comment la cohérence temporelle et spatiale des particules lagrangiennes peut améliorer l’efficacité des algorithmes de suivi. Nous avons contraint l’algorithme à suivre l’information basée sur la physique des mouvements cohérents puisque les particules traceuses lagrangiennes se déplacent localement et se comportent de manière cohérente avec leurs voisins. Nous avons utilisé le concept de structures cohérentes lagrangiennes (LCS) sur des trajectoires lagrangiennes éparses pour déterminer les mouvements cohérents locaux des flux turbulents. Les LCS présentent des crêtes de ligne/surface (frontières) dans les écoulements 2D/3D qui séparent les régions d’écoulement ayant des trajectoires dynamiquement différentes. Par conséquent, nous pouvons quantifier les trajectoires cohérentes et non cohérentes des voisins en fonction des crêtes LCS. Dans cette thèse, l’idée d’utiliser les mouvements cohérents locaux des particules lagrangiennes a été discutée dans trois algorithmes de vélocimétrie. Nous avons montré comment les mouvements cohérents peuvent augmenter la robustesse des techniques d’initialisation des trajectoires. Ensuite, l’idée a été employée pour améliorer la performance de la prédiction. Enfin, l’approche proposée a été adaptée et appliquée aux algorithmes classiques de PIV.</dcterms:abstract>
     <dcterms:abstract xml:lang="en">We present here a study that attempts to improve velocimetry algorithms by using the temporal and spatial coherency of Lagrangian particles. As Lagrangian tracer particles move and behave coherently with their neighbours, we constrained the algorithm to comply with physics-based information. In order to determine local coherent motions of turbulent flows, we utilized Lagrangian Coherent Structures (LCS) over sparse Lagrangian trajectories. In 2D/3D flows, LCS has line/- surface ridges separating regions with dynamically different trajectories. Based on LCS ridges, we can quantify coherent and non-coherent neighbour trajectories. Three velocimetry algorithms are discussed in this thesis using the idea of local coherent motions of Lagrangian particles. Through coherent motions, we demonstrated how the track initialization techniques in time-resolved three-dimensional particle tracking velocimetry (4D- PTV) can become more robust. This idea was then used to improve prediction performance. We also explored how to apply this approach to classic PIV algorithms.</dcterms:abstract>
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       <tef:nom>Rahimi Khojasteh</tef:nom>
       <tef:prenom>Ali</tef:prenom>
       
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                        <dc:identifier xsi:type="tef:NNT">2022REN1S084</dc:identifier>
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