Experimental study on the behavior of thermally insulated RC beams strengthened with CFRP after their exposure to high temperatures compared to non- insulated ones
Bibliographic record
Abstract
With regard to the expansion of the use of carbon fiber reinforced polymer (CFRP) in strengthening civil engineering structures due to its high positive points (like high tensile strength and low thickness) as well as its weaknesses in high temperatures especially in buildings and weak points of existing thermal insulators, the experiments mentioned in this article have been carried out to investigate the post-fire conditions of CFRP retrofitting systems using the externally bonded reinforcement technique which resulted from the need to use insulation for this type of reinforcement system to improve its heat performance, as well as the weak points of common insulations. In the first phase, 12 samples of reinforced concrete (RC) beams strengthened with externally bonded carbon fiber reinforced polymer (UD200) were heated at 400 °C, 500 °C, 600 °C, and 800 °C and loaded after cooling, then they were compared with the results of the second phase of the tests which have been explained completely, consisting of 11 RC beams strengthened with CFRP having exactly the same properties as those in the first phase. They were also thermally insulated with intumescent paint that had some advantages like low thickness (1.1 mm) and the speed and ease of implementation and restoration. These results have clearly shown that the new insulating layer not only can maintain the positive feature of common insulations, but also unlike other common insulators, does not add to the thickness of the specimens. Moreover, the application of the intumescent paint both increased the performance of the specimens at high temperatures and covered the weaknesses of CFRP reinforcement system against heat so that the CFRP sheets unlike the ones on the non-insulated specimens did not completely disappear at the highest temperature.
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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) | 0.000 | 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) | 0.002 | 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".