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Record W7161966237 · doi:10.82308/4322

Development of seismic vulnerability maps using ambient vibrations and GIS

2013· dissertation· en· W7161966237 on OpenAlexaboutno aff
Salman Saeed

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsModalVulnerability (computing)VibrationDisplacement (psychology)SoftwareSeismic riskVulnerability assessmentSynchronization (alternating current)

Abstract

fetched live from OpenAlex

The goal of this study is to examine the possibility of reducing the epistemic uncertainties in seismic vulnerability estimation methods, particularly when properties of simplified models utilized in these methods are fitted to those obtained, for example, from Ambient Vibration Tests (AVTs) inter alia carried out on specified buildings without much prior knowledge on their characteristics and structural details. A seismic evaluation procedure was developed that utilizes the modal parameters of buildings extracted from AVT to construct a shear buildings model of the building and uses the maximum inter-story drift due to an earthquake as the performance index. The spectral displacement at the fundamental frequency of the buildings is used as the ground motion parameter to characterize the earthquake. Seismic Vulnerability of a building is expressed as the probability of passing the threshold of 'slight damage' by considering limits on inter-story drift as defined in the HAZUS MH-MR4. The procedure was applied to twenty four medium to high rise buildings located in Downtown Montreal and a GIS software was used to generate the spatial distribution of seismic vulnerability on a map. One of the aims of this study is to reduce the time and cost of carrying out AVTs for application to a large of number of buildings. In this regard, the synchronization of data obtained in AVT is of utmost importance since the extraction of modal parameters depends on the correlation of responses between various nodes. Ensuring synchronization through hardware means is often expensive yet unreliable, especially in case of large buildings. In this study a novel data processing method is proposed to synchronize the data recorded on separate data acquisition systems. Application of this method is demonstrated by conducting AVT on Jacues Bizzard Bridge in Montreal and several buildings in Downtown Montreal. The National Building Code of Canada (NBCC 2010) requires that torsional modes be included in the dynamic analysis of buildings and that the deflection of the two points located on the periphery of the building be used for calculating the inter story drifts. Also investigated in this study are various sensor deployment schemes using a numerical model for simulation of AVT in order to determine the optimal deployment scheme that can capture torsional modes of the buildings while keeping the time and cost of the AVT at a minimum.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.243
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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