Optical Fiber Chloride Sensor for Health Monitoring of Structures in Cold Regions
Bibliographic record
Abstract
The ever-increasing need to maintain aging existing reinforced concrete structures, especially in severe winter environments, in good condition and a cost-effective manner arises mainly in structural health monitoring methods, where it is necessary to adopt approaches that allow early detection of corrosion. Chloride-induced corrosion is a significant durability issue in cold regions where de-icing salts are used. This paper presents an embedded optical fiber chemical sensor that detects reliable free chloride concentrations into concrete cover in a precise non-destructive manner. It is based on fluorescence measurements using a chloride-sensitive fluorescent calcium-alginate sol-gel. Optical fibers were not affected by environmental factors, ions presences, or cold climate. Nevertheless, the fluorescent chemical sensor showed sensitivity towards alkalinity, temperature, leaching, and photo-bleaching. These restraints were encountered by applying a successfully validated ratiometric fluorimetry approach. Also, the durability and long-term stability of the sensor were studied. This sensor detects low chloride concentrations in a range of 0.045–0.45 M present in pore solution. It demonstrates a robust behavior, and excellent long-term stability so that it can withstand harsh environments. Thus, this sensor could provide a new approach towards the rapid, simple, and non-destructive monitoring of the structural health for detected the onset of corrosion damage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".