Newtonian and non-Newtonian two-phase flow in complex pipelines
Notice bibliographique
Résumé
Two-phase gas/non-Newtonian fluid flow through pipes commonly occurs in many industrial applications, such as in the chemical industry and oil and gas refineries. Many fluids used in oil and gas industries display non-Newtonian behaviour. Their rheology strongly affects pressure drop, flow structure, interface fluctuation, void fraction, heat transfer, and other flow features. In fact, non-Newtonian systems are not governed by the Newtonian law of viscosity. However, little experimental work has been devoted to studying non-Newtonian flow behaviour. This present work has conducted an experimental investigation to understand the fundamental physics of non-Newtonian two-phase (gas/ liquid) flow through pipes. In the experiments, several concentrations of Xanthan Gum were used as the non-Newtonian liquid, and both compressed air and carbon dioxide were used as gases. The flow rate and pressure of liquid and gas are changed by using a pump placed ahead of the mixing point. Pressure values are recorded by pressure sensors fixed at specific points along the pipe loop, and more than 10,000 experimental data points have been collected. The Experimental data analysis went through four categories. The first part is to calibrate all pressure sensors. The second step was applying rheology tests on our non-Newtonian Fluid to define the fluid behaviour and estimate the fluid properties. The third goal is to develop a new model for estimating pressure drop for the gas/non-Newtonian flow. The last part of the experiments is void fraction measurements. Pressure drop is one of the most challenging concerns related to industrial process design. In fact, multiphase flow process design depends on a better understanding of multiphase flow regimes. Numerous research has been done on gas/Newtonian liquid flow in horizontal and vertical pipes in the past few decades. Still, only a few research studies have been carried out to identify gas/non-Newtonian flow regimes. [1]. Creating a new model to estimate void fraction for gas-non-Newtonian flow is another objective done in the present work. The void fraction is considered one of the most important flow parameters used to describe two-phase flows in tubes. Void fraction is an important process variable for the volume and mass calculation required to transport gas-liquid mixture in pipelines, storage in tanks, metering, and custody transfer. Furthermore, it is important to determine other flow parameters such as two-phase density and viscosity or the average velocities of gas and liquid mixture. In addition, it plays a significant role in estimating and modelling two-phase pressure drop and flow pattern transitions. The created void fraction model is used to determine constants of general form posted by Butterworth[2]. Both developed void fraction models give a good estimation for the void fraction with about 5% percent errors compared with our experimental results and other available literature experimental results.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), 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 ».