Development of a Mathematical Model for Monitoring Recovery Boiler Dissolving Tank Sounds
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Notice bibliographique
Résumé
In the chemical recovery process of kraft pulp mills, molten smelt falls into the dissolving tank where it interacts violently with hot water. These smelt-water interactions allow for fast smelt dissolution, however too many violent interactions can also cause equipment damage. In severe cases, violent smelt-water interactions may result in dissolving tank explosions, costing millions of dollars to pulp mills. One way to monitor smelt-water interactions within the dissolving tank is through the sound they generate. In this work, an acoustic model of smelt-water interaction was developed to examine dissolving tank sound characteristics and operating factors affecting the sound intensity. Field studies were conducted to obtain acoustic data at several mill sites. Laboratory experiments were then conducted to study each part of the smelt-water interaction process. The results of field measurements and laboratory experiments allowed for better understanding of the physical mechanisms involved in smelt-water interactions in the dissolving tank. This model is stochastic in nature and describes the physical processes from the moment molten smelt droplets enter water to the acoustic signals produced by numerous vapour bubble expansions and collapses. Each component of the model was verified through empirical data. The simulation results of the integrated model were then compared against acoustic measurements taken from mill visits. The model predictions were in good agreement with the sounds recorded from pulp mills under various operating conditions. The model could also accurately predict other mill variables such as the temperature of green liquor in the dissolving tank based on acoustic signals. In addition, the model provides predictions of changes within the dissolving tank when parameters such as smelt droplet size distributions and smelt flow rate are varied. The results obtained through these simulations show trends that are in agreement with findings from other studies. The results also suggest that dissolving tank water temperature, smelt flow rate, and smelt droplet size are amongst the most important factors in the intensity of explosion events. The model and algorithmic procedures developed in this thesis work may be used to develop an acoustic monitoring system for recovery boiler dissolving tanks.
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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) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| 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) | 0,001 | 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 découle