Computational Fluid Dynamic Modeling of a Hydraulic Flocculator for the Charles-J.-Des Baillets Water Treatment Plant (City of Montreal)
Bibliographic record
Abstract
RÉSUMÉ: «RÉSUMÉ: Cette étude vise à fournir une solution durable et résiliente pour faire face aux impacts négatifs du changement climatique sur la qualité de la source d'eau de l'usine de traitement d'eau Charles-J.-Des Baillets. Une fréquence accrue d'orages peut entraîner des augmentations significatives de la turbidité certains jours, entraînant une diminution de l'efficacité du processus de filtration. Par conséquent, l'utilisation d'un floculateur hydraulique avant la filtration directe est proposée pour améliorer l'élimination de la turbidité et prolonger la durée des cycles de filtration. L'analyse du fonctionnement et de l'efficacité de ce floculateur avec deux configurations (8 ou 16 chicanes) a été réalisée en utilisant la Dynamique des Fluides Numérique (CFD) à travers OpenFOAM, en plus d'une étude expérimentale pour définir la cinétique de croissance des flocs selon le nombre de Camp (Gt). Les résultats indiquent que l'ajout de chicanes en amont des filtres peut créer efficacement la perte de charge nécessaire pour effectuer la floculation hydraulique. De plus, l'analyse de la vélocité a révélé des variations distinctes des schémas de flux et des longueurs de recirculation, la configuration à 16 chicanes montrant un flux plus cohérent et contrôlé, impactant potentiellement l'efficacité globale de la floculation. En examinant le gradient de vélocité (valeur G), la configuration à 16 chicanes réduit significativement la plage de 10 s-1 à 500 s-1, indiquant un meilleur contrôle du flux par rapport à la plage plus large, de 10 s-1 à plus de 1000 s-1, observée dans le canal à 8 chicanes. De plus, une évaluation qualitative du nombre de Camp (Gt) illustre une augmentation notable de Gt après l'ajout de chicanes, le Gt actuel dans le canal sans chicane étant inférieur à 10,000, tandis que le canal à 16 chicanes connaît des valeurs de Gt plus élevées de 53,000, et la configuration à 8 chicanes a une valeur de Gt de 26,000 à la sortie du floculateur, ce qui correspond à la plage inférieure de Gt généralement utilisée.» ABSTRACT: «ABSTRACT: This study aims to provide a sustainable and resilient solution to address the adverse impacts of climate change on the water source quality of the Charles-J.-Des Baillets water treatment plant. Increased occurrence of storms may lead to significant increases in turbidity on certain days leading to a decreased efficiency of the filtration process. Accordingly utilizing a hydraulic flocculator prior to direct filtration is proposed to improve turbidity removal and increase the length of filtration cycles. Analyzing the function and efficiency of this flocculator with two configurations (8 or 16 baffles) was performed utilizing Computational Fluid Dynamics (CFD) through OpenFOAM in addition to an experimental study to define flocs growth kinetics according to the Camp number (Gt). The results indicate that adding baffles upstream from the filters can effectively create the necessary head loss to perform hydraulic flocculation. Moreover, velocity analysis revealed distinctive flow pattern variations and recirculation lengths, with the 16-baffle setup demonstrating a more consistent and controlled flow, potentially impacting overall flocculation efficiency. Examining velocity gradient (G value), the 16-baffle configuration significantly narrows the range to from 10 s-1 to 500 s-1, indicating superior flow control compared to the wider range, 10 s-1 to over 1000 s-1, observed in the 8-baffle channel. In addition, qualitative assessment of Camp number (Gt) illustrates a notable Gt increase after adding baffles, the current Gt in the channel without baffle is lower than 10,000, while the 16-baffle channel is experiencing higher Gt values of 53,000 and the 8-baffle setup has the Gt value of 26,000 at the flocculator exit, which aligns with the lower range of typically used Gt.»
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".