MétaCan
Menu
Back to cohort
Record W4226020114 · doi:10.1590/1679-78257023

Effects of Non-Structural Walls on Mitigating the Risk of Progressive Collapse of RC Structures

2022· article· en· W4226020114 on OpenAlex

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.

Bibliographic record

VenueLatin American Journal of Solids and Structures · 2022
Typearticle
Languageen
FieldEngineering
TopicStructural Response to Dynamic Loads
Canadian institutionsMcMaster University
FundersKing Saud University
KeywordsInfillStructural engineeringProgressive collapseFinite element methodDisplacement (psychology)Reduction (mathematics)Materials scienceGeotechnical engineeringEngineeringReinforced concreteMathematicsGeometry

Abstract

fetched live from OpenAlex

This study aims to investigate the effect of the infilled frames through various important parameters (i.e., the openings’ percentage in infill walls - several columns on the first floor are removed - partial infilled) in the RC structures, subject to progressive collapse scenarios. To this end, 3D finite element models were constructed by using the software ABAQUS. Numerical and experimental results were compared to substantiate the finite element models’ capability of simulating the experimental models’ behavior of Al-Chaar et al. (2002) in an accurate manner. The results showed that there was good agreement between experimental and numerical results. Moreover, the results indicated that there was a significant effect, which cannot be neglected, on the progressive collapse resistance; the reduction ratios in vertical displacement at the regions removed columns can reach up to 80%.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.789
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.003
GPT teacher head0.221
Teacher spread0.218 · 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