Non-Destructive Assessment and Remedy of Grouted Prestressed Cable Ducts in Post-Tensioned Decks
Bibliographic record
Abstract
Post-tensioned concrete bridge decks have been in service in Ontario for more than 30 years. Many of such bridge deck have been operating without any waterproofing/asphalt protection from their initial construction. Concerns currently exist as to the condition of the prestressing cables in the grouted ducts, particularly in the negative moment regions where the cables are closest to the deck surface. Deterioration of post-tensioned bridge decks due to prestress cable corrosion is matter of considerable concern since the repair or replacement is proved to be a costly process. As Ontario bridge infrastructure enters the era of maintenance, rehabilitation and replacement, there is an urgent need for investigating non-destructive inspection methodologies or procedure to assess the conditions of the grouted ducts and cables inside without invasive concrete work involving major concrete removal to expose the ducts for visual inspection. As such, the main objectives of this research were to (i) conduct state-of-the-art and state-of-practice review on the available non-destructive testing (NDT) techniques; (ii) conduct laboratory testing on simulated bridge deck segments with grout-encased prestressing cables to evaluate promising candidate method identified from the literature review that may be applicable to detect voids in the ducts, cable fracture or corrosion in post-tensioned decks; and (iii) propose a remedial procedure to fill the detected voids with grouting materials. Eight concrete specimens were caste to investigate the applicability of selected NDT methods on locating the reinforcing steel bars, ducts, corrosion in cables and voids. These methods were (i) Ground Penetration Radar ; (ii) Impact-Echo ; and (iii) Half-cell Potential. Also, Remedial procedure using vacuum grouting was experienced to fill the detected voids.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 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".