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Record W4411940026 · doi:10.1139/cjce-2024-0578

Degrading seismic performance of tall shear wall buildings under earthquake sequences

2025· article· en· W4411940026 on OpenAlexvenueno aff
Ali Ruzi Özuygur

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicSeismic and Structural Analysis of Tall Buildings
Canadian institutionsnot available
Fundersnot available
KeywordsShear wallSeismic analysisStructural engineeringSeismic retrofitSeismic hazardGeologyGeotechnical engineeringSeismic loadingEarthquake scenarioEngineeringForensic engineeringSeismologyReinforced concrete

Abstract

fetched live from OpenAlex

It is widely recognized that high-seismic regions across the world are frequently affected by repeated earthquakes. The destructive effects of repeated earthquakes have been investigated by many researchers using performance parameters such as residual displacement, inter-story drift, and dissipated energy. In this study, a high-rise reinforced concrete shear wall building with 40 floors above grade, which represents a typical real tall building, is selected as the example building for numerical analyses. Nonlinear response history analyses are performed under different combinations of earthquakes with various spectral acceleration intensities. The analysis results for the tall building under the earthquake sequences indicate that concrete strain governs the seismic performance level of the building, while steel strain consistently meets the immediate occupancy limit. The study concludes that the immediate occupancy threshold, defined by the concrete strain at peak stress, is a critical limit for preventing significant damage under repeated seismic demands.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.177
Teacher spread0.172 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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