A methodology for assessing the seismic risk of buildings
Notice bibliographique
Résumé
Many infrastructure networks rely on each other to deliver utilities and services to the community. In the event of a disaster, these networks can sustain significant damage. It is therefore important to identify interdependencies among networks to mitigate the disaster consequences. In 2003, Public Safety Canada (PSC) and NSERC initiated the Joint Infrastructure Interdependencies Research Program (JIIRP) for this purpose. The research was carried out at six Universities across Canada including the University of British Columbia (UBC). The aim of JIIRP at UBC was to study infrastructure interdependencies during disasters in order to aid in decision making. This involved the development disaster simulation methodology and tool, and the implementation of a case study. UBC's Point Grey campus was used as case study. The campus is located in southwestern British Columbia, a known seismic zone, therefore earthquake disaster scenario was chosen. Reasonable estimations of the expected seismic damage and losses are required in order to simulate a realistic disaster scenario. For this reason, in this thesis, seismic risk assessment was carried out for the buildings at UBC. This involved the development of a building database, the assessment of the expected level of damage to the structural and nonstructural building components, and the estimation of monetary, human and functionality losses. Buildings in the database were classified into prototypes and the damage was estimated for several levels ofintensity using damage probability matrices. As expected, the most vulnerable buildings on campus were those containing unreinforced masonry. These buildings make up 7% of the buildings on campus. The least vulnerable buildings were multi-family residential woodbuildings which account for 27% of the buildings on campus. Losses were estimated following the damage assessments. Casualties were estimated for three times of day. 2PM was determined to be the critical time of day as the campus population is the greatest at this time. Monetary loss and functionality trends were examined with respect to earthquake intensity and it was shown that for moderate intensity earthquakes, the losses depend primarily on nonstructural damage, while structural damage plays the most important role for higher intensities.
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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 ».