Notice bibliographique
Résumé
Increased urbanization causes pervious greenfields to be converted to impervious areas increasing stormwater runoff. Most of the urban floods occur because existing drainage systems are unable to handle peak flows during rainfall events. During a storm event, flood runoff will carry contaminants to receiving waters such as rivers and creeks. Engineers and scientists have combined their knowledge to introduce innovative thinking to manage the quality of urban runoff and harvest stormwater for productive purposes. The introduction of pervious pavements addresses all the principles in Water Sensitive Urban Design. A pervious pavement is a load bearing pavement structure that is permeable to water. The pervious layer sits on the top of a reservoir storage layer. Pervious pavements reduce the flood peak as well as improve the quality of stormwater at source before it is transported to receiving waters or reused productively. To be accepted as a viable solution, understanding of the influence of design parameters on the infiltration rate (both from the bedding and the sub-base) as well as strength of the pavement requires to be established. The design of a particular pavement will need to be customized for different properties of sub layer materials present in different sites. In addition, the designs will have to meet local government stormwater discharge standards. The design of drainage systems underneath pervious pavements will need to be based on the permeability of the whole pervious system. The objectives of the research project are to: • Understand the factors influencing infiltration capacities and percolation rates through the pervious surface as well as the whole pavement structure including the bedding and the sub-base using a laboratory experimental setup. • Obtain relationships between rainfall intensity, infiltration rate and runoff quantity based on the sub-grade material using a computational model to assist the design of pervious pavements. A laboratory scale pavement was constructed to develop relationships between the surface runoff and the infiltration volume from a pervious pavement with an Eco-Pavement surface. 2 to 5mm crushed gravel and 5 to 20mm open graded gravel were chosen as the bedding and sub-base material. Initial tests such as dry and wet density, crushing values, hydraulic conductivity, California Bearing Ratio tests for aggregate material were conducted before designing and constructing the pavement model. A rainfall simulator with evenly spaced 24 sprays was set up above the pervious pavement surface. The thesis presents design aspects of the laboratory scale pavement and the tests carried out in designing the pavement and the experimental procedure. The Green and Ampt model parameters to calculate infiltration were obtained from the laboratory test results from aggregate properties. Runoff results obtained from rainfall simulator tests were compared with the Green and Ampt infiltration model results to demonstrate that the Green and Ampt parameters could be successfully calculated from aggregate properties. The final infiltration rate and the cumulative infiltration volume of water were independent of the rainfall intensity once the surface is saturated. The model parameters were shown to be insensitive to the final infiltration capacity and to the total amount of infiltrated water. The Green and Ampt infiltration parameters are the most important parameters in designing pervious pavements using the PCSWMMPP model. The PCSWMMPP model is a Canadian model built specially for designing pervious pavements. This is independent of the type of sub-grade (sand or clay) determining whether the water is diverted to the urban drainage system (clay sub-grade) or deep percolation into the groundwater system (sand sub-grade). The percolation parameter in Darcy's law is important only if the infiltrated water recharges the groundwater. However, this parameter is also insensitive to the final discharge through the subgrade to the groundwater. The study concludes by presenting the design characteristics influencing runoff from a pervious pavement depending on the rainfall intensity, pavement structure and sub-grade material and a step-by step actions to follow in the design.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 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 | 0,000 | 0,001 |
| 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 ».