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Enregistrement W6940553532 · doi:10.7939/r3-sr0x-nk29

Development of Prediction Tools for Improved Wear Assessment of Pipelines and Complex Geometries

2021· dissertation· en· W6940553532 sur OpenAlexaboutno aff

Notice bibliographique

RevueUniversity of Alberta Library · 2021
Typedissertation
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueMycorrhizal Fungi and Plant Interactions
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPipeline transportSlurryErosionPipeline (software)Flow (mathematics)Computational fluid dynamicsCompletion (oil and gas wells)Visualization

Résumé

récupéré en direct d'OpenAlex

Particle-laden flows such as pneumatic conveying or slurry transport are common in the minerals processing and oil sands industries. These industries face the challenge of erosion wear due to the repeated impact of the entrained particles, and subsequent damage to pipelines and equipment. Many economic losses such as equipment replacement cost, start-up and shutdown cost, and loss in production are associated with this erosion wear. An estimated $1 billion/year in losses has been reported for the Canadian oil sands industry alone. It is, therefore, important for industries to know when and where failure will occur, as well as how much material is lost in order to take proactive steps to reduce these losses. The goal of this thesis is to develop more accurate predictive tools and methodologies that industries can use to assess the wear performance of their processes. Bench-scale devices and wear models are the typical predictive tools which will be explored in this thesis. Part I of this thesis focuses on the development of a bench-scale device known as the toroid wear tester (TWT) as a slurry pipeline wear prediction tool. An initial Computational Fluid Dynamics (CFD) analysis and flow visualization experiments were conducted to study the hydrodynamics in the TWT. The results revealed regions of strong secondary flows in the TWT, and further identified possible operating conditions for wear testing which may be scalable to horizontal slurry pipelines applications. A subsequent experimental investigation studied how the bed of particles respond to the TWT hydrodynamics. Coulombic stress was correlated to measured wear rate in the device over a range of operating conditions. It was found that a fully settled slurry flow regime occurs in the TWT when the ratio of the linear wheel speed to the particle terminal settling velocity is less than 7, and that there is a linear correlation between the measured wear rate and Coulombic stress in this region. However, to apply this correlation to slurry pipelines, the amount of wear due to Coulombic stress in pipelines must also be calculated. A CFD and experimental data analysis were therefore conducted on slurry pipeline wear data as a follow-up study. The results revealed that a correlation similar to that obtained for the TWT also exists in slurry pipelines between Coulombic stress and the associated wear rate. More slurry pipeline wear data are needed to further develop and support the correlation that would allow the use of the TWT for the prediction of wear in slurry pipelines. Part II of this thesis presents studies on the improvement of wear model performance in complex geometries, and for effective decision-making in industrial process operations. The first study used CFD modelling to develop a geometry correction factor function (GCFF) for a standard 90-degree elbow. The GCFF provides factors that correct the effect of geometry-induced secondary flows not originally accounted for in the development of traditional single particle erosion models. The GCFF in this study was combined with the Oka erosion model and it performed better than the model alone. Another CFD analysis was conducted on a Once-Through Steam Generator (OTSG) system used in in situ oil sands extraction. Superheated steam transports precipitated fine particles (10 microns) at very low concentration (3 ppm) in the OTSG boiler tubes. Contrary to previous assumptions, the investigation showed severe erosion wear damage in the boiler tubes due to these fine particles. Additional analysis showed that the API RP 14E industrial guideline used in the design of OTSGs cannot adequately capture the effect of operational changes such as an increase in steam production rate. The CFD analysis performed was, however, able to show that a 10% increase in OTSG operating velocity would cause failure in the OTSG boilers two times faster. In summary, a significant step towards accurate wear prediction in slurry pipelines and other particle-handling systems was made though the research presented.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Méthodes · Signal consensuel: Méthodes
Score de désaccord entre enseignants0,007
Score d'incertitude au seuil0,014

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

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.

Tête enseignante Opus0,018
Tête enseignante GPT0,211
Écart entre enseignants0,194 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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