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Record W2139215291 · doi:10.1139/cjce-2012-0098

Analysis of a damaged 12-storey frame-wall concrete building during the 2010 Haiti earthquake Part I: Dynamic behaviour assessment

2013· article· en· W2139215291 on OpenAlexaffvenue
Benoı̂t Boulanger, Charles‐Philippe Lamarche, Jean Proulx, Patrick Paultre

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsRead Jones Christoffersen (Canada)Université de Sherbrooke
Fundersnot available
KeywordsStructural engineeringFinite element methodVibrationDamagesAmbient vibrationNormal modeRepresentation (politics)Frame (networking)Mode (computer interface)EngineeringComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

Despite all the damages encountered during the 2010 Haiti earthquake, the 12-storey reinforced-concrete Digicel building behaved well, sustaining only reparable damages. Visual assessment to characterize the damages sustained and ambient vibration tests (AVT) were carried out to identify the building’s key dynamics properties (natural vibration frequencies, mode shapes, and damping ratios). ETABS was used to generate finite element (FE) models before and after the AVT, to evaluate the capabilities of common modelling assumptions to predict the dynamic behaviour of structures. Nonautomated model updating was carried out to generate a model representing the building’s actual dynamic behaviour in its damaged state. The study showed that the finite element method (FEM) is reliable for predicting the dynamic behaviour of structures, but is very sensitive to the modelling assumptions. The models could predict the vibration frequencies precisely, but an accurate representation of the mode shapes required careful model updating.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.731
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2013
Admission routes2
Has abstractyes

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