Experimental Investigation on the Rehabilitation of RC Flat Slabs Using CFRP Sheets to Enhance Punching Shear Capacity
Bibliographic record
Abstract
In this paper, the feasibility of strengthening a flat column–slab connection within the carbon fiber reinforced polymer (CFRP) has been investigated through experimental study. The experimental program includes a set of nine reinforced concrete flat slab specimens. Three unaltered specimens served as control slabs, while an additional six samples were strengthened with various CFRP configurations to enhance their shear capacity. The strain distribution, ductility, punching shear resistance, stiffness, and crack formation were studied. The result of experimental studies showed that in the direct method of strengthening in which two layers of unidirectional CFRP sheets were employed in two opposite directions, the ultimate punching shear resistance improved by 64%, 44.7%, and 15.3%, with respect to the location of the column connection, as compared with the control specimens. In the case of using one layer of unidirectional CFRP strips, the punching shear resistance was enhanced by approximately 16% and 39%, considering the configuration of CFRP sheets and the amount of strengthened and adhesive layers used. Following the outcomes of this research, the application of CFRPs in improving the resistance capacity of flat slabs against the punching shear is considerable. The reported outcomes were compared with the latest provisions of ACI to show the efficiency of the presented strengthening. Finally, a parametric study was performed assuming different loading locations to assess the effect of the loading region on the response of RC slabs. Results indicate that approaching the loading location toward the RC slab supports results of an increase in the load-bearing capacity and a reduction in the ductility of the RC slab.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".