Assessment of the CFRP–Concrete Interface Integrity of Original Champlain Bridge Diaphragms through Nondestructive and Semidestructive Testing
Bibliographic record
Abstract
Externally bonded fiber-reinforced polymer (FRP) composites have been widely adopted for the rehabilitation of aging bridge infrastructure in recent decades. The major reasons for the utilization of these materials in bridge rehabilitation include strength, durability, lightweight nature, design flexibility, and quick installation. However, deterioration of the bonded interface between the concrete substrate and the FRP—or between individual layers of a multilayer composite—can significantly impact the structural performance of the strengthened member or system. Therefore, it is necessary to evaluate the effectiveness and accuracy of condition assessment techniques to ensure satisfactory performance over the intended service life of the structure. This paper presents a visual inspection and detailed assessment of three full-size diaphragms from the Champlain Bridge in Canada. The diaphragms were strengthened with externally bonded carbon fiber–reinforced polymer (CFRP) sheets 5 years before the bridge was decommissioned as a result of extensive degradation after 57 years in service. The condition assessment includes nondestructive (acoustic tapping and infrared thermography) and semidestructive (direct pull-off) testing to identify surface and subsurface issues including CFRP delamination, material incompatibility, discoloration due to corrosion, interfiber cracks, and fundamental problems arising from the construction of the bridge diaphragms and installation of the CFRP. The results of 490 pull-off tests, comprising the largest single database of its kind to date, generally confirmed the results of nondestructive tests that aimed to locate hidden defects behind the strengthening layers. Microscopy of failed surfaces provides additional insights into the condition of the bond line in defective regions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".