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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 OpenAlexaff
Ali Altheeb, Ibrahim M.H. Alshaikh, Aref A. Abadel, Moncef L. Nehdi, Hussam Alghamdi

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.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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

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 designBench or experimental
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

Citations31
Published2022
Admission routes1
Has abstractyes

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Same venueLatin American Journal of Solids and StructuresSame topicStructural Response to Dynamic LoadsFrench-language works237,207