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Record W2461340914 · doi:10.1139/cjce-2016-0326

Developing a plastic hinge model for reinforced concrete beams prone to progressive collapse

2018· article· en· W2461340914 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicStructural Response to Dynamic Loads
Canadian institutionsConcordia University
Fundersnot available
KeywordsProgressive collapseStructural engineeringPlastic hingeHingeChord (peer-to-peer)Finite element methodNonlinear systemMoment (physics)Reinforced concreteDuctility (Earth science)EngineeringMaterials scienceComputer sciencePhysics

Abstract

fetched live from OpenAlex

It is known that building structures would undergo nonlinearity during progressive collapse. Given this, modelling the nonlinear behaviour of structural members is critical for assessing their resistance. The objective of this study is to develop the nonlinear modelling parameters of reinforced concrete (RC) beams for the progressive collapse analysis. To achieve this, three types of RC moment-resisting buildings located in high, moderate, and low seismic zones in Canada are designed. Nonlinear pushdown analyses are then conducted on 27 three-dimensional finite element models using ABAQUS to examine the case that one column on the ground level is removed. Based on the analysis results, an idealized moment-rotation curve for modelling the plastic hinge in beams with different ductility is proposed. In comparison with the 2013 GSA modelling parameters, smaller chord rotations are observed from the detailed finite element analysis.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.636
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.011
GPT teacher head0.216
Teacher spread0.205 · 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