Effect of Environmental Parameters on Atmospheric Corrosion of Carbon Steel Infrastructures in Montreal, Qc, Canada: past, Current and Future Scenarios
Bibliographic record
Abstract
Abstract Atmospheric corrosion plays a critical role in structural metal loss and thus infrastructure service life. Since the 1920's, many studies have focused on the effect of environmental parameters on the corrosion of major construction metals and it has been shown that chlorides, pollutants in the air such as sulfur dioxide, temperature, and relative humidity are the main environmental factors affecting the corrosion rate. Several studies have come up with a dose response function to predict the corrosion rate of a specific metal based on the environmental factors it is exposed to. The predicted corrosion rate is a critical design factor to secure safe and reliable infrastructure performance during its design service life. Therefore, future climatic changes in the environment may need to be considered when selecting a proper material and its required thickness as changes in environmental factors due to climate change in certain regions may affect the corrosion rates. Currently, historical data is used for designing infrastructures without considering the future climatic changes. This study summarizes the effort on atmospheric corrosion programs involving Canada's climate and illustrates the changes in corrosion rate of carbon steel in the City of Montreal over the past 70 years and up to 80 years in the future using the projections of climatic models. The goal is to demonstrate the effect of climate change and the variation in atmospheric exposure conditions for future durability designs of infrastructures such as bridges against atmospheric corrosion.
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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".