Water Velocity Distribution and Its Impact on the Performance of an Electrocoagulation Reactor for Drinking Water Treatment
Notice bibliographique
Résumé
Iron electrocoagulation (EC) is a promising alternative to more expensive chemical coagulation for remote communities that frequently face boil water advisories[1]. In EC, the iron anode dissolves in water producing iron hydroxide and other iron-based species that facilitate the removal of natural organic matter (NOM), as per the reactions below: Anode: Fe(s)→Fe z+ (aq)+ze - Cathode: 2H 2 O(l)→H 2 (g)+2OH - (aq) Solution: Fe z+ (aq)+zOH - (aq)+xNOM(aq)→Fe(OH) z (NOM) x (s) The current density distribution in an EC cell is heterogeneous due to the local variation of [Fe z+ ] and its effect on the local anodic equilibrium potential, according to the Nernst equation. Therefore, the reactor hydrodynamics affect current density distribution and the resulting performance of the EC cell. This research focused on the theoretical and experimental analyses of the velocity distribution within a pilot scale EC reactor. The steady-state water velocity distribution was simulated using COMSOL Multiphysics. The flow turbulence was simulated using the k-ε model. The reactor walls and the open interface with air were modeled as no-slip and slip boundaries, respectively. Water entry and outlet were modeled as constant flow and constant gauge pressure boundary conditions, respectively. Model validation was performed using partial electrode assembly design, similar to the work of Stumper et al [2]. Segments of the EC reactor were masked by an adhesive, insulating Kapton sheet. Masking of the electrode limited the reaction to the uncovered portions, while not interfering with the hydrodynamics of the reactor.[3] The modeling results show the water velocity distribution in the cell, which leads to removal of [Fe z+ ] from the electrode/electrolyte interface and shifts the electrochemical equilibrium potential. This shift leads to a variation in the distribution of iron dissolution in the reactor. The results also indicate that the flow homogeneity increases with an increase in the inter-electrode distance, as well as with a decrease in water flow rate. Partial electrode assembly experiments verified the simulation results for a range of inter-electrode distances and water flow rates. Figure 1 shows a typical water velocity distribution, current mapping in the reactor, and comparability of the simulation and experimental results. The validated model shows the heterogeneity in flow distribution and can predict the useful lifetime of an iron electrode before its substitution or break off due to accelerated corrosion in specific areas. Such predictions enable optimum capacity, design, and operation for the reactor. The results of this project can lead to improved electrocoagulation of water for NOM removal, which can benefit communities that rely on surface water sources. References: S. Vasudevan and M. A. Oturan, Environ. Chem. Lett. 12 , 97 (2014). J. Stumper, S. A. Campbell, D. P. Wilkinson, M. C. Johnson, and M. Davis, Electrochim. Acta 43 , 3773 (1998). S. T. Mcbeath, Pilot-Scale Iron Electrocoagulation for Natural Organic Matter Removal, University of British Columbia, 2017. Figure 1
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».