Multiphase Modeling of a Flowing Electrolyte-Direct Methanol Fuel Cell
Notice bibliographique
Résumé
Direct methanol fuel cells (DMFCs) are considered one of the leading contenders for low power applications due to their energy dense, liquid fuel as well as low greenhouse gas emissions.However, DMFCs have lower than predicted performance due to methanol crossover.One proposed solution is to allow a liquid electrolyte, such as diluted sulfuric acid, to flow between the anode and cathode, thereby removing any methanol that attempts to crossover to the cathode.The corresponding fuel cell is named the flowing electrolyte -direct methanol fuel cell, or FE-DMFC.So far few researchers have examined the effectiveness of this fuel cell and none have explored the multiphase flow within the membrane electrode assembly (MEA) of this fuel cell.In this study, the well-known Multiphase Mixture Model (MMM) was improved with a new single domain approach which was used to model the flow behaviour and performance of the FE-DMFC.Unlike the existing methods, the proposed model only requires the mixture variables, thereby removing the requirement for information about the gaseous state, when attempting to couple the porous and electrolyte layers together.Furthermore, the model's formulation gives the capability to resolve liquid saturation jumps in a single domain manner.The proposed approach is sufficiently flexible that it could be applied to other modeling methods, such as the Multi-Fluid Model (MFM).The corresponding derivation for the MFM is provided.The fidelity of the improved MMM is examined through 3 test cases, which include a comparison to: the analytical liquid saturation jump solution, the analytical single phase solution for the FE-DMFC, and to in-house FE-DMFC experimental iii First and foremost, I would like to thank my supervisors, Dr. Edgar Matida and Dr. Cynthia Ann Cruickshank, for giving me the opportunity to work on this project.Their patience, support and guidance towards my work and their open door policy are greatly appreciated.Whenever we met, they always displayed enormous enthusiasm and passion towards teaching and research and I found it very contagious.I would also like to thank Dr. Feridun Hamdullahpur for his support and generosity in the initial years of my work and Dr. Glenn McRae for his invaluable input and for our many fruitful discussions in the area of electrochemistry.We would frequently lose track of time during these discussions.Over the years, he has been an incredible wealth of information in seemingly everything.I would also like to thank the technologists and machinists at Carleton University for their help and guidance in my experimental work.As well as Neil McFadyen for his help in giving me access to the computational resources on campus and for his technical support.I would also like to extend a special thanks to
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) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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.
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 ».