Shear Strengthening of Concrete Deep Beams with Geopolymer-Based Fabric-Reinforced Matrix Composites
Bibliographic record
Abstract
Test results of three large-scale reinforced concrete (RC) deep beam specimens with a shear span-to-depth ratio (a/h) of 1.6 are reported in this paper.One control beam was not strengthened whereas two beams were strengthened in shear using one layer of unidirectional carbon fabric-reinforced matrix (CFRM) composites.A geopolymeric matrix was used in the CFRM of one of the strengthened specimens to examine its potential use as a sustainable alternative to a commercial cementitious mortar.The geopolymeric matrix was a mixture of ground granulated blast furnace slag and fly ash activated by an alkaline solution consisting of sodium silicate and sodium hydroxide.The control beam failed shortly after initiation of a diagonal splitting shear crack in the shear span.The strengthened beams failed at a higher load in a shear-compression or diagonal tension mode of failure.Shear strengthening with CFRM composites resulted in a shear strength gain of 95% when a cementitious mortar was used as a matrix.The use of CFRM with a geopolymeric matrix was effective in improving the shear response but to a lesser extent.The gain in shear capacity caused by CFRM with a geopolymeric matrix was 77%.
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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".