Measurement techniques to characterize bubble motion in swarms
Notice bibliographique
Résumé
A technique was developed to study the effect of surfactant (frother) on individual bubble motion in swarms. The technique was based on high speed cinematography and tracking of multiple moving objects. Image processing algorithms were implemented in Matlab to isolate and measure geometric properties of the bubbles in image sequences recorded at 1 ms interval; and these properties were compiled into a data structure. To track a bubble, the geometric properties and a matching criterion were applied on consecutive pictures to identify the bubble. The bubble trajectory was reconstructed from the data structure for the matched objects. To maximize the number of bubbles identified from an image, de-clustering algorithms were developed and validated. A new shape factor model for ellipsoidal objects and a correction model for pixelation effect were developed. To characterize the level of bubble interaction in a swarm, a technique for measuring average dimensionless bubble inter-distance was developed. To characterize the effect of frother type on bubble surface a new technique for measuring surface flows (Marangoni effect) on a bubble blown in air was developed. The results provided experimental evidence of the mechanisms by which surfactants dampen bubble oscillation and reduce bubble terminal rise velocity and helped to interpret the frother type effect. Experiments to determine the effect of surfactant (concentration and type), bubble interactions and bubble size distribution type on bubble velocity in swarms were conducted using the bubble tracking technique in a rectangular transparent column (12x5x140 cm) with an inclined top section (15°). A flat bubble swarm was generated combining a slot (60 mm x 60 microm) and porous-slot (60 x 1.1 mm) spargers. These combinations allowed the generation of bubble size distributions similar to those in industrial flotation machines. Bubble images were collected at three locations (near the point of generation, the top of the straight section and in the inclined section) to track the impact of surfactant accumulation. The results showed that the presence of surfactant reduced bubble coalescence and breakage and stabilized the bubble surface. As a consequence, the bubble size distribution remained stable as the swarm rose. Experimental measurements of bubble motion in the presence of surfactants showed for both single bubbles and swarms, that surfactant accumulation occurs as the bubbles detach from the generating point, and the impact occurs gradually, determined by the subsequent evolution of bubble aspect ratio. The bubble tracking measurements revealed a velocity-size profile, which was determined by: the predominant bubble size class, bubble interactions (dimensionless bubble inter-distance), and the surfactant type and concentration. The surfactant type seems to be a factor in determining bubble rise velocity for bubbles below 0.8 mm, despite the theory that surface mobility for such small bubbles in unaffected by surfactants. It is thus proposed that surface viscosity plays a role on bubble motion. The new techniques for bubble motion and surface characterization were tested for bubble swarms in presence of Polyglycol and Pentanol. Two contributions to the knowledge emerging from this phase of the work are: (a) bubble motion in swarm describes a bubble velocity-size profile with a high dependency on the bubble distribution type, and (b) surfactant type influences bubble rise velocity for bubbles in range 0.1 to 4 mm.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».