Prediction of Temperature and Concentration Profiles in an Industrial Polymerization Fluidized Bed Reactor under Condensed-Mode Operation
Notice bibliographique
Résumé
Condensed mode operation of gas-phase ethylene polymerization adds more complexity to the hydrodynamics of fluidized bed reactors (FBRs). This study aims at the development of an industrial ethylene polymerization FBR model operating in condensed mode, and in this regard, the classical two-phase theory was modified. Two modeling strategies were investigated: a simple two-phase model (model I) and a more complex one taking the presence of a wet zone (model II) into consideration. To access the predictive capabilities of the two models, model predictions were compared with plant data. The absolute relative deviation percentages for model I in prediction of the production rate and catalyst flow rate were 10.4 and 14.8, respectively. However, these errors for model II were 0.80 and 10.36, respectively. It was observed that the temperature profile predicted by model I was more consistent with that of plant data when the bubble diameter was considered to be small because of enhanced heat transfer rates between the bubble and emulsion phases. However, this assumption was not necessary for model II, and assuming a maximum stable bubble diameter for bubbles in the reactor, which is a more realistic assumption, the predicted temperature profile was reasonable. According to the results of model II, two zones, wet (including liquid droplets) and dry (including evaporated liquid), are formed in the condensed-mode operation of FBRs. It was found that for low-condensing agent flow rates (70 ton/h in this study), the difference between process conditions (concentration and temperature) of wet and dry zones increases (Δ C = 22.16 mol/m 3 and Δ T = 40.19 K), which can produce bimodal polyethylene (PE). Furthermore, a search strategy was developed based on the imperialist competitive algorithm and model II to find polymerization conditions needed to produce a PE grade with a specified microstructure. The results showed that the proposed algorithm is efficient for such a purpose. The sensitivity analysis of model I proved that in low gas velocities, the emulsion phase temperature is very sensitive to the catalyst flow rate. Moreover, the results of model I demonstrate that the dependency of temperature and monomer concentration of the emulsion phase on particle elutriation is negligible, especially under normal operating conditions.
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 | 0,001 |
| 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 | 0,001 | 0,001 |
| 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 ».