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Record W2260631542 · doi:10.11575/prism/2189

Flat slabs: the influence of the slab thickness and the stud layout

2004· dissertation· en· W2260631542 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePRISM (University of Calgary) · 2004
Typedissertation
Languageen
FieldEngineering
Topic3D Modeling in Geospatial Applications
Canadian institutionsnot available
Fundersnot available
KeywordsSlabStructural engineeringMaterials scienceEngineering drawingEngineering

Abstract

fetched live from OpenAlex

The objective of this work was to investigate the influence of the slab thickness and the layout of shear stud reinforcement on the behaviour of interior slab-column connections. To achieve this, experiments on 12 interior slab-column connections were conducted having the slab thickness and the layout of shear reinforcement as their major variables. The tests were designed using the shear friction model for slabs developed by Dechka (2001). The test results were included in a database developed to investigate the strengths and weaknesses of the shear friction model and the current Canadian design code (CSA Standard A23.3-94, 1994). The experimental program revealed a dependency of the punching capacity of interior slab-column connections on the slab thickness. The experiments also helped to identify rational patterns for shear reinforcement placement and allow for recommendations on the extent of such shear reinforcement. In the course of the theoretical investigation, the shear friction model was further developed to better reflect the actual punching behaviour of slab-column connections. The development mainly focuses on the location and shape of the failure cone. Due to the unsatisfactory performance of the current Canadian design code in the comparison of its punching load predictions to experiments on over 300 slab-column assemblies, recommendations are made to improve this design code. The recommendations are made in a form that they can be adapted easily to the current Canadian code.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.004
GPT teacher head0.180
Teacher spread0.175 · 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