Channel deformation, turbulence structure around spur dike, and reduction of local scour at bridge abutments using spur dikes under ice-covered conditions - an experimental study
Notice bibliographique
Résumé
,Local scour around bridge abutments and piers presents a significant challenge in hydraulic engineering, threatening the structural integrity of bridges. Scour refers to removing sediment around bridge foundations due to high-velocity flow and turbulence from water passing around these structures. This process can undermine the stability of bridges by exposing and weakening their foundations, potentially leading to failures and catastrophic collapses. Several factors contribute to scour, including water flow characteristics, surface conditions, hydraulic structure features, and riverbed geomorphology. Effective mitigation of scour is essential to ensure bridge safety and longevity. Traditional methods, such as riprap, concrete aprons, and various hydraulic structures, aim to alter flow patterns and reduce erosive forces. However, these methods can be constrained by environmental conditions and site-specific characteristics. This research explores using spur dikes, hydraulic structures extending from the riverbank to redirect the flow, to mitigate local scour at bridge abutments, especially under ice cover conditions. The study utilizes a large-scale outdoor hydraulic flume at the Quesnel River Research Center in British Columbia, Canada. The flume measures 38.5 meters in length, 2 meters in width, and 1.3 meters in depth, with a longitudinal bed slope of 0.2% to replicate natural flow conditions with non-uniform flow characterized by longitudinal variations in water depth. Two sandboxes are filled with natural sediments of different median grain sizes (0.48 mm, 0.60 mm, and 0.90 mm) to replicate riverbed conditions. Spur dikes made from marine plywood were positioned upstream of the abutment (25 cm and 50 cm) and at different alignment angles (45º, 60º, 90º) in the flume. Abutments constructed from galvanized plates were installed in the sandboxes. Styrofoam panels simulated smooth and rough ice cover conditions, with smooth panels representing natural sheet ice and rough panels mimicking ice jams through attached Styrofoam cubes. Flow rate and water depth were measured using a SonTek-IQ Plus, an advanced instrument with six sensors for comprehensive flow field coverage and high-accuracy data collection. Acoustic Doppler Velocimetry (ADV) captured detailed 3D velocity components and turbulence intensities, measuring the velocity of scattering particles in the flow to provide insights into complex flow dynamics around the spur dikes and abutments. This experimental study aims to enhance understanding of scour dynamics by investigating the interactions between different spur dike configurations, flow conditions, and ice cover types. It provides detailed insights into how these factors influence local scour and sediment transport processes. Additionally, the study seeks a comprehensive understanding of the flow field and 3D velocity distribution around spur dikes under various conditions, analyzing the effects of different alignment angles and ice cover on flow patterns and turbulence structure, which are critical for predicting and mitigating scour. Another goal is to develop effective scour mitigation strategies, identifying optimal configurations that provide maximum protection under various hydraulic and environmental conditions. Overall, the combined studies aim to advance the field of hydraulic engineering by offering practical solutions for mitigating scour-related risks, thereby ensuring the stability and safety of bridge abutments in diverse hydraulic environments.
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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 | 0,000 |
| 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 ».