Investigation & Mitigation of Corroding Unbonded Post-Tension Tendons
Bibliographic record
Abstract
Abstract Unbonded post-tension (PT) tendons have been used for many years to reinforce concrete structures. Generally, these structures have performed well except where unbonded PT tendons have suffered from corrosion due to moisture penetration or protective grease deficiencies. Like other technologies, unbonded PT systems have evolved and improved over the years from “paper-wrap” to “push-through” to “heat sealed” to “extruded” to “fully encapsulated” systems. Consideration should be given to the type of system when selecting the appropriate evaluation and corrosion mitigation methods for these systems. Evaluation of unbonded post-tensioned structures is important to determine the current condition and to determine if corrosion and deterioration is likely to occur. If broken tendons or corrosive conditions are identified, a suitable mitigation strategy should be implemented such that the structural integrity can be maintained, and the service life of the structure can be met or extended. This paper will discuss the types of unbonded PT structures which exist, evaluation techniques which can be used to identify the presence of corrosion, and mitigation methods which have been developed to mitigate corrosion of unbonded PT tendons. Project case studies will be presented to demonstrate the applicability and effectiveness of these techniques.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".