Analytical modeling of concrete columns confined by FRP
Bibliographic record
Abstract
FRP-encased concrete columns benefit from a confining effect due to the restraint of the lateral expansion. This effect increases the strength and the ductility of the concrete inside the FRP shell. A number of empirical models predicting the behaviour of steel- and FRP-confined concrete have been presented in literature. However, a more accurate model for FRP-confined columns is needed. This thesis proposes a model for concrete columns confined by an FRP shell, where the axial load is applied to the concrete core only and the shell is used as a confining jacket. A second model is proposed for the case where both the FRP and the concrete carry the compressive axial load. The latter model is modified to include configurations with an inner centered void and configurations with a double shell. All of these models satisfy the conditions of equilibrium and strain compatibility between both materials. Also a finite element model for FRP-confined columns, based on the Drucker-Prager criterion, is presented. The proposed models are verified by comparing the predictions to experimental data published by different researchers, including an experimental program carried out at the University of Manitoba. The proposed models are used to examine the influence of key parameters, believed to determine the behaviour of composite sections.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".