ANALYTICAL METHODOLOGY FOR SIZING PHASE CHANGE MATERIAL THERMAL ENERGY STORAGE UNDER SYSTEM BOUNDARY CONDITIONS
Notice bibliographique
Résumé
The expanding use of renewable and sustainable energy systems is at the forefront of the global effort to reduce CO2 emissions and mitigate climate change. Thermal energy storage has become a critical component of many of these new and innovative systems, and research in this field has expanded to meet their requirements. Water has been traditionally used as a storage medium because of its high heat capacity and low cost, but depending on the application, the storage volume requirements may be excessively large. Phase Change Materials (PCMs) offer an opportunity to reduce the storage volume through latent energy storage. However, energy storage in PCM presents new challenges, and careful design of thermal storage is required to realize the benefits. The design of PCM storage must consider the system operation, operating temperature range, PCM properties, encapsulation, and the heat transfer fluid. In the current state-of-the-art literature, there is no standard method for designing PCM thermal storage based on system requirements. The objective of this thesis is to deliver a methodology to assess the feasibility of using PCM for thermal energy storage in place of water. This is done by identifying which applications benefit from PCM, comparing the analytical and numerical performance of water-only to hybrid water-PCM storage, and developing a method to size PCM containment to achieve theoretical performance when PCM is beneficial. This research study develops analytical solutions for sizing PCM thermal energy storage based on system boundary conditions. These boundary conditions consist of the system itself (e.g. heat pump, absorption chiller), the energy source into the system, and the required load from the system (e.g. a building). The PCM is incorporated into a water tank such that the water acts as both a heat transfer fluid and an energy store. Analytical predictions of the total energy storage capacity in this hybrid water-PCM thermal storage unit are coupled to analytical predictions of the rate of melting and solidification to appropriately determine the required volume and encapsulation thickness of PCM thermal storage based on the system requirements. The results are verified against full-system numerical simulations based on case studies of solar absorption cooling and heat-pump heating. It is shown in this study that the total required volume of storage is a function of the temperature differential of the system, and the total mismatch in time between when energy is available and when it is required. A mathematical formulation is proposed which quantifies the required storage volume based on the temperature differential, the source and load profiles, and the percentage of PCM in the hybrid water-PCM storage unit. Furthermore, the rate of melting and solidification of the thermal storage is coupled to the overall storage size and required time for charging, and a mathematical formulation is proposed which solves for the PCM encapsulation thickness. The method assumes a conservative conduction-dominated domain and demonstrates how complete melting can be ensured before the system reaches its maximum allowable temperature. The map the region of applicability of PCM thermal storage is also presented which is defined in terms of the non-dimensional Biot and Stefan numbers, in which systems utilizing PCM thermal storage will benefit from volume reduction when compared to using water only. This region is characterized with a low Biot number, corresponding to a slender geometry acting as a lumped system, as well as a low Stefan number, corresponding to limited temperature differential and limited sensible energy storage. These characteristics favor the use of PCM thermal storage instead of water only. This thesis presents a novel contribution to the state-of-the-art literature in PCM thermal storage, which is established through the analytical methodology for sizing PCM thermal storage based on system boundary conditions. The details of the contribution are presented in the form of three journal publications that have been integrated into this sandwich Ph.D. thesis on PCM thermal energy storage.
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 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 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 | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,028 | 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 ».