Dual estimation of iron oxide deposition on drinking water PVC pipes using calibrated turbidity data and brightfield microscopy in a full-scale laboratory system
Notice bibliographique
Résumé
The assessment of accumulated sediments inside drinking water pipes is an important step for determining the risk of water quality deterioration for a sector of a distribution network and for scheduling the required maintenance activities that minimize this risk. Water utilities and researchers have traditionally used turbidity data collected during flushing operations to quantify the discolouration potential in isolated pipe lengths. Flushing has an elevated cost of specialized personnel, consumes large quantities of drinking water, and offers poor information about sediment conditions prior to mobilization (e.g. structure, position on the pipes). The last problem must be overcome by gaining a better understanding of the processes driving material accumulation, which might help in the development of strategies to prevent sediment deposits. In addition, a complex relationship between turbidity and SSC also makes it difficult to accurately translate turbidity units (NTU) into physical units of concentration (e.g. mg/L). This paper aims to consolidate the macroscopic estimations of sediment deposits in drinking water pipes using turbidity data and to propose a microscopic complement that provides richer data about sediment deposits at the pipe wall. The research was developed through a controlled experiment using a full-scale PVC pipe system that mimics the operational conditions of drinking water distribution systems. In the experiments, the drinking water was amended with iron oxide particles that progressively adhered to the pipe walls during 30 days of steady flow conditioning. After the conditioning period, the pipes were flushed to mobilize the sediment deposits. The SSC of water samples collected during the experiments were used to produce translation factors for the online turbidity data. Macroscopic sediment loads were estimated based on the difference between suspended sediments at the inlet and outlet of the pipe loop, while microscopic loads were estimated through the direct observation of particles on pipe wall samples using automated brightfield microscopy. Physical metrics were proposed to adequately represent the sediment load data. Results from the turbidity data analysis produced insights about the impacts of experimental conditions on the SSC translation factors, while microscopy images allowed a detailed assessment of particles deposited on the pipe walls including information about their particle size distribution and dispersion.
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 | 0,000 | 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 ».