Experimental and numerical study of the reinforcement of reinforced concrete bridge decks by adherent overlaying
Bibliographic record
Abstract
The work developed in this report is part of research programme of the University of Sherbrooke, the purpose of which is to make technical recommendations for the durable repair of slabs of bridge deck. Following a bibliographical synthesis, we led a study in laboratory to analyze the structural behaviour of reinforced concrete slabs repaired using an adherent overlaying. The experimentation rested on a pilot slab and four slabs overlay according to different configurations (thickness of concrete, reinforcemen steel, anchorings). These slabs underwent several cycles of static and cyclic loading in pure bending in order to follow their behaviors in time. The experimental results made it possible to appreciate the good performance of three of the four configurations on the debonding of repair and the structural behavior of the slabs. To consolidate the noted were used two computer codes by finite elements (MSC., MARC/MENTAT, ABAQUS 6.4.1) for, on the one hand, reproducing and to validate structural slabs repaired and for, on the other hand, analysing comprise it the constraints generated on the interface support-overlaying. The whole of the work realised within the framework of this thesis makes it possible to propose new techniques of repair of slabs of reinforced concrete bridge decks
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".