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Record W4416862914 · doi:10.1061/jsendh.steng-15235

Collapse Risk of Tall Nonductile Reinforced Concrete Shear Wall Buildings

2025· article· en· W4416862914 on OpenAlex
Preetish Kakoty, Carlos Molina Hutt, Kenneth J. Elwood

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Structural Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsShear wallReinforced concreteSeismic riskFragilityInduced seismicityGround motionSeismic analysisSeismic hazardProgressive collapse

Abstract

fetched live from OpenAlex

Existing buildings, particularly those predating modern building codes, pose significant seismic risk in regions of high seismicity worldwide. In the City of Vancouver, British Columbia, Canada, reinforced concrete shear wall (RCSW) buildings are prevalent in the construction of tall buildings. Many of these buildings were constructed before the introduction of ductility requirements in the Canadian concrete standard during the mid-1980s, and they predominantly serve as residences for renters, seniors, and low-income populations. This study quantifies the collapse risk of these tall nonductile RCSW buildings to understand their seismic vulnerability. Leveraging a comprehensive database of pre-1980 RCSW buildings, a framework is proposed to generate representative archetypes using a random forest regression model. An automated workflow is developed to facilitate nonlinear structural analyses of these buildings, and a sample of 25 archetypes of varying heights, i.e., 10–30 stories, is selected to evaluate their seismic performance. The results indicate a high risk of collapse, ranging from 9% to 29% in 50 years, significantly higher than the collapse risk target of 1% in 50 years in US standards. The results also indicate that collapse risk can be significantly underestimated when (1) taxonomy-level fragility functions are employed to characterize the performance of this unique typology of buildings, and (2) when the ground motion amplification effects of the Georgia sedimentary basin below Metro Vancouver are neglected.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.003
GPT teacher head0.193
Teacher spread0.190 · 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