Experimental and Analytical Analysis of Perimeter Radiant Heating Panels
Notice bibliographique
Résumé
In recent years the U. S. and Canada have seen a steady increase in energy consumption. The U. S. in particular uses 25% more energy than it did 20 years ago. With declining natural resources and an increase in fuel costs, it has become important to find methods of reducing energy consumption, in which energy conservation in space heating and cooling has become a widely researched area. One method that has been identified to reduce the energy required for space heating is the use of radiant panels. Radiant panels are beneficial because the temperature set points in a room can be lowered without sacrificing occupant comfort. They have therefore become very popular in the market. Further research, however, is required to optimize the performance of these panels so energy savings can be realized. An analytical model has been developed to predict the panel temperature and heat output for perimeter radiant panel systems with a known inlet temperature and flow rate, based on a flat plate solar collector (RSC) model. As radiative and convective heat transfer coefficients were required to run the model, an analytical analysis of the radiative heat transfer was performed, and a numerical model was developed to predict the convective heat transfer coefficient. Using the conventional radiative heat exchange method assuming a three-surface enclosure, the radiative heat transfer could be determined. Numerically, a correlation was developed to predict the natural convective heat transfer. To validate the analytical model, an experimental analysis was performed on radiant panels. A 4m by 4m by 3m test chamber was constructed in which the surrounding walls and floor were maintained at a constant temperature and the heat output from an installed radiant panel was measured. Two radiant panels were tested; a 0. 61m wide panel with 4 passes and a 0. 61m wide panel with 8 passes. The panels were tested at 5 different inlet water temperatures ranging from 50°C to 100°C. The RSC model panel temperature and heat output predictions were in good agreement with the experimental results. The RSC model followed the same trends as that in the experimental results, and the panel temperature and panel heat output were within experimental uncertainty, concluding that the RSC model is a viable, simple algorithm which could be used to predict panel performance.
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 | 0,001 | 0,001 |
| 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 | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».