Modeling Tsunamis for Improved Hazard Assessment and Detection
Notice bibliographique
Résumé
This body of work uses state of the art numerical models to assess and reduce tsunami hazard. The first manuscript describes the use of these models to explore nonlinear interaction between tide and tsunami in the context of hazard assessment. Inundation due to several probable maximum tsunamis (PMTs) is considered in the Hudson River Estuary (HRE). Of the sources considered, a submarine mass failure (SMF) poses the most significant tsunami threat in this region and across the entire US East Coast. The next manuscript focuses on the how SMF mechanics effect tsunami generation. In addition to inundation, SMF tsunamis are dangerous because of their short or nonexistent warning times. The final manuscript discusses developments to an algorithm which extend the range of tsunami detection by shore-based HF radar, thereby increasing warning times. Tsunami hazard assessment in the Hudson River Estuary based on dynamic tsunami-tide simulation. The first manuscript is part of a tsunami inundation mapping activity carried out along the US East Coast (USEC) since 2010, under the auspice of the National Tsunami Hazard Mitigation program (NTHMP). Two densely built low-lying regions are situated along this coast: Chesapeake Bay and HRE. HRE is the object of this work, with specific focus on assessing tsunami hazard in Manhattan, the Hudson River and East River areas. Modeling coastal tsunami hazard from submarine mass failures: effect of slide rheology, experimental validation, and case studies off the US East coast. We first validate two models simulating tsunami generation by deforming submarine mass failures (SMFs) against laboratory experiments for SMF made of glass beads moving down a steep slope. These are two-layer models, in which the upper layer is water, simulated with the non-hydrostatic 3D non-hydrostatic model NHWAVE, and the SMF bottom layer is simulated with depth-integrated equations and represented either as a dense Newtonian fluid or a granular medium. At most nearshore locations surface elevations caused by the rigid slump are significantly larger (up to a factor of 2) than those caused by the 3 deforming slides. Hence, the rigid slump provides a conservative estimate of SMF tsunami impact in terms of maximum inundation/runup at the coast, while using a more realistic rheology with some level of SMF deformation, in general, leads to a reduced tsunami impact at the coast. This validates as conservative the tsunami hazard assessment and inundation mapping performed to date as part of NTHMP, on the basis of Currituck SMF proxies simulated as rigid slump. Algorithms for tsunami detection by High Frequency Radar : development and case studies for tsunami impact in British Columbia, Canada. To mitigate the tsunami hazard along the shores of Vancouver Island in British Columbia (Canada), Ocean Networks Canada (ONC) has been developing a Tsunami Early Warning System (TEWS), combining instruments (seismometers, pressure sensors) deployed on the sea floor as part of their Neptune Observatory, and a shore-based High-Frequency (HF) radar. The authors have proposed a new detection algorithm based on spatial correlations of the raw radar signal at two distant locations along the same wave ray. In a previous work, they validated this algorithm for idealized tsunami wave trains propagating over a simple sea floor geometry in a direction normally incident to shore. In the final manuscript, this algorithm is extended and validated for realistic tsunami case studies conducted for seismic sources and using the bathymetry off of Vancouver Island, BC. (Abstract shortened by ProQuest.)
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 | 0,000 |
| 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) | 0,000 | 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 ».