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Record W2060867870 · doi:10.1061/9780784413357.092

Staged Failure Mechanism of Aged RC Beam-Columns Subjected to Corrosion Loads Using Simplified Nonlinear Finite Element Model

2014· article· en· W2060867870 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

VenueStructures Congress 2014 · 2014
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsNational Research Council CanadaUniversity of Ottawa
Fundersnot available
KeywordsStructural engineeringFinite element methodBeam (structure)CorrosionMaterials scienceNonlinear systemStiffnessFailure mechanismDisplacement (psychology)Drop (telecommunication)Flexural strengthStructural loadEngineeringComposite materialPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

An analysis approach to simulate the staged failure mechanism of corrosion-affected beam-column subjected to ultimate or seismic load using a simplified, non-linear, finite element model is proposed. The instantaneous axial and flexural rigidities at the sectional level are transferred to the element level, establishing the instantaneous structure stiffness at each load step. The approach efficiency and accuracy are verified through comparison with available experimental and analytical results. The proposed approach is numerically stable in all studied cases. It is found that the staged failure mechanism of the columns subjected to quasi-static load and cyclic load up to failure can be simulated with high accuracy. It is also found that corrosion-induced damage results in a large drop of the column load and displacement capacities, and a large shrinkage in the hysteretic relationship, which indicates similar drop in the energy absorption capacities of the beam-columns.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score1.000

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 studies0.0000.000
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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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