Long-term monitoring of a CFRP-wrapped concrete column
Bibliographic record
Abstract
Fibre-reinforced polymer laminates are now used on a regular basis for repairs to concrete members. The laminates can be wrapped around an entire member or applied to any portion once the member has been repaired and its surface properly prepared to receive the laminate. However, two questions have arisen as to the suitability of the laminates in affecting a satisfactory long-term repair for concrete members; namely,i) Do the laminates alter the properties of the concrete or the chemical environment within the concrete, which is critical to the survival of the steel reinforcement? ii) How well and for how long do the laminates bond to repaired and original concrete surfaces? To obtain some answers to these questions, the performance of a pair of square concrete columns has been monitored since 1996. The columns straddle an expansion joint within a heated multi-level, underground parking garage in Gatineau, Quebec. About a year after extensive repairs were made to the concrete structure, one column was completely covered with a carbon fibre-reinforced polymer (CFRP) and the second left in its reconditioned state to serve as the control for the study. A data acquisition system comprising a multi-channel data recorder and an array of relative humidity and temperature sensors and strain gauges was installed to continuously monitor conditions in the columns. In addition, annual non-destructive electro-chemical and sonic surveys were conducted on the columns to assist in examining the effects of the laminate. As pull-off tests on the wrapped column were undesirable because of the need to patch and reseal tested areas, a set of concrete specimens, divided into garage and control samples, was coated with the laminate and tested yearly to monitor pull-off strength. This paper will present the data collected during the past six years and discuss the effects of the laminate on the conditions and properties of a concrete.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".