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Enregistrement W4396870631 · doi:10.59490/coastlab.2024.809

Large-Scale Laboratory Experiments On The Wave Generation Due To The Collapse Of Partially And Fully Submerged Granular Columns

2024· article· en· W4396870631 sur OpenAlexaff
Erica Treflik-Body, Elisabeth Steel, W. Andy Take, Ryan P. Mulligan

Notice bibliographique

RevueProceedings of the ... International Conference on the Application of Physical Modelling in Coastal and Port Engineering and Science. · 2024
Typearticle
Langueen
DomaineEngineering
ThématiqueEarthquake and Tsunami Effects
Établissements canadiensQueen's University
Organismes subventionnairesnon disponible
Mots-clésScale (ratio)MechanicsGranular materialGeologyGeotechnical engineeringMaterials sciencePhysics

Résumé

récupéré en direct d'OpenAlex

Landslides that occur in coastal environments can drive cascading consequences such as wave forces, flooding, and infrastructure damage to coastal communities. It can be difficult to classify these slides as subaerial or submarine, and the mechanics of wave generation associated with partially submerged failures are not well understood. Limited physical modelling has been conducted that encompasses both the triggering of granular landslides and subsequent waves associated with partially and fully submerged mass movements. To date, laboratory work investigating tsunamis generated by submarine landslides has focused on the wave formed in the direction of the mass movement (seaward direction) for rigid block experiments (eg. Rzadkiewicz, 1997) and deformable slide masses (e.g. Grilli et al., 2017, Takabatake, 2020, Bullard et al., 2023). From these experimental data sets, predictive relationships connecting slide acceleration, mass, and initial submergence depth to the amplitude of the wave formed have been presented for the seaward wave. Such relationships have not been presented for the landward directed wave, which propagates in the opposite direction of the submarine landslide motion. Further, not all landslides are easily classified as either subaerial or submarine. Consider the 2018 Anak Krakatoa landslide in which the sliding surface was estimated to be 100 m below sea level (Pakoksung et al., 2020), resulting in one third of the total collapse being submerged. In comparison to the end-member conditions of subaerial and submarine failures, the mechanics of wave generation associated with partially submerged failures is much less clear. Granular column collapse experiments provide an idealized experimental framework to explore momentum transfer processes and the resulting waves generated in partially submerged and fully submerged conditions. Work by Cabrera et al., (2020) made use of granular collapse experiments of partially to fully submerged columns to derive a continuous momentum-based function to estimate the maximum seaward wave amplitude based on the initial column submergence ratio (Hw/Ho). However, these experiments were conducted at a small-scale (Ho = 0.15 m) with a width of one particle (2.4 mm diameter). To address this research gap, a series of 22 large-scale granular collapse experiments were conducted by releasing columns of river stone (0.75 m and 0.50 m high) into a laboratory flume reservoir with water depths ranging up to 1.10 m to explore the wave generation and runup processes in both seaward and landward directions. The columns were released by a rapid pneumatically actuated vertical rising gate designed to enable the near instantaneous loss of support of the source volumes resulting in granular collapse. The failure mechanics were captured with high-speed cameras (Figure 1a,b) and wave amplitudes were measured using wave capacitance gauges (Figure 1c,d). This work also provides the first experimental data set of the landward propagating wave and runup associated with submerged granular collapse experiments. Overall, the seaward wave amplitudes measured in these highly-instrumented, large-scale physical models agree with empirical relationships developed in a previous study using smaller-scale models.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,751
Score d'incertitude au seuil0,186

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,020
Tête enseignante GPT0,230
Écart entre enseignants0,211 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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Même revueProceedings of the ... International Conference on the Application of Physical Modelling in Coastal and Port Engineering and Science.Même sujetEarthquake and Tsunami EffectsTravaux en français237 207