Flexural strengthening of reinforced concrete beams with basalt fibre reinforced polymers
Bibliographic record
Abstract
This thesis presents the experimental results of laboratory testing conducted on full-scale concrete beams which were strengthened with Basalt Fibre Reinforced Polymer (BFRP) fabrics.The goal was to determine the viability of using external BFRP fabric reinforcement to strengthen flexurally controlled concrete members in-situ. The use of BFRP as an external strengthening material is compared to other materials such as glass (GFRP) and carbon (CFRP) fabrics which are currently widely accepted strengthening materials. Two parameters were varied during the research: the internal steel reinforcement ratio, and the external BFRP layers, to study the interaction between the two. Using BFRP showed excellent results as a flexural strengthening method. The moment capacity of the strengthened beams was found to increase by up to 79% over the control beam for the yield strength, and by up to 120% over the control for the ultimate strength.The yield deflection of the strengthened beams remained similar to the control beam without much reduction or increase, and the ultimate load deflection was increased by up to 140% over the control specimen. This is a key finding as previous tested discussed in the literature review found that both the yield and ultimate deflections of strengthened beams was greatly reduced when using GFRP and CFRP fabrics. When compared to the applicable Canadian and American FRP design guidelines, it was found that the Canadian code needs to be updated to reflect the same process used to determine the FRP design strain used in the American code. With this update, both codes can accurately predict the strength increase found in these specimens. When strengthening flexural members with BFRP fabrics, the beams exhibit increased load-deflection stiffness. It is recommended to also strengthen the beams shear capacity when flexurally strengthening a concrete member to maintain beam integrity and ductility.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".