On Bond-slip of EB-FRP/Concrete Interface in Shear Under Fatigue Loading: Review and Synthesis of Experimental Studies and Models
Bibliographic record
Abstract
Reinforced concrete (RC) structures subjected to cyclic fatigue loading are prone to progressive damage. Among the types of structural damage, those leading to shear deficiencies can result in sudden rupture of structures without warning. Hence, RC structures deficient in shear urgently need retrofitting. The use of externally bonded (EB) fiber-reinforced polymer (FRP) composites presents many advantages and is a very promising technology for shear strengthening of RC structures. This paper encompasses a wide range of research findings related to the interaction between concrete and FRP under fatigue loading. The behavior of the bond between FRP and concrete plays a major role in the failure mode of FRP shear-strengthened structures especially under fatigue. Therefore, it is of interest to characterize the FRP/concrete interaction using appropriate models with respect to the influencing parameters. The paper will first discuss existing design guidelines and considerations related to the fatigue behavior of RC structures. A thorough review of available literature on EB-FRP/concrete bond in shear under cyclic fatigue loading will then be presented, with a focus on proposed bond-slip models and finite element studies of the FRP/concrete interface under fatigue loading.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".