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Record W2096553017 · doi:10.1061/9780784413357.072

Finite Element Analysis of a Reinforced Concrete Slab-Column Connection using ABAQUS

2014· article· en· W2096553017 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
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSlabStructural engineeringPunchingFinite element methodReinforced concreteShear (geology)ReinforcementColumn (typography)Materials scienceConnection (principal bundle)EngineeringComposite material

Abstract

fetched live from OpenAlex

Reinforced concrete flat slabs are used worldwide as a construction system in many multistory buildings. The problem that can occur in flat slabs is high stresses in the slab-column connection area that can result in a punching shear failure. Nonlinear Finite Element analyses can be performed in order to investigate the phenomenon of punching shear and to gain information on slab behavior. In this paper, a 3-D analysis of the reinforced concrete slab with the finite element software ABAQUS using the damage-plasticity model is presented. The choice of the adequate material model is important in finite element modeling for concrete structures. The simulations of the reinforced concrete slab are compared to the behavior of a specimen that has been tested at the University of Waterloo. This study involves the investigation on the punching shear behavior of reinforced concrete slab-column connections without shear reinforcement. The results of the FEA simulations indicate the reasonable response when compared to the behavior of the test specimen. The simulations give information on the punching shear capacity and the crack pattern.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
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
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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