Behavior of BFRP Bars in Moist Geopolymer Concrete and Alkaline-Exposed Conventional Concrete
Bibliographic record
Abstract
This research studies the performance of sand-coated basalt fiber reinforced polymer (BFRP) in two different environments under varied temperatures conditioned for 3 months.During the conditioning period, these BFRP specimens were subject to two environmental conditioning schemes: moist geopolymer concrete and alkaline solution simulating the concrete pore solution.The conditioning temperature varied among 20, 40, and 60C.Both types of concrete were designed with a nominal cylindrical compressive strength of 40 MPa with a slag-to-fly ash mass ratio of 1:3.The tensile strength, moisture uptake, and matrix retention of BFRP bars were measured.Test results highlighted the tensile strength of BFRP bars submerged in moist geopolymer concrete decreased significantly, retaining 68.3%, 47.6%, and 57.9% at 20C, 40C, and 60C, respectively.In contrast, BFRP bars in the alkaline solution showed superior tensile performance with retention of 95.4%, 97.1%, and 91.2% at the same conditioning temperatures.All tested bars in moist geopolymer concrete exhibited higher moisture uptake compared to those in the alkaline solution.At 20C, the moisture uptake was nearly double in geopolymer concrete, and this trend continued at higher temperatures.This indicates a higher rate of water diffusion in geopolymer concrete, which accelerates degradation mechanisms such as hydrolysis.The matrix retention of BFRP bars was significantly lower in moist geopolymer concrete, especially at elevated temperatures, suggesting greater susceptibility to resin matrix degradation in this environment.These results highlight the crucial influence of the surrounding concrete environment on the long-term performance of BFRP bars
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 teacher head, 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".