Pyrrhotite in concrete aggregate. Introduction to mechanism, damage potential and ongoing research
Bibliographic record
Abstract
Pyrrhotite is an iron sulfide which when present in concrete aggregate may lead to expansive reactions, cracks and finally disintegration of the concrete. This potential risk when using aggregates containing sulfides in concrete production has been known for several decades, and international concrete standards take this into account. Though, recent examples of deterioration of concrete structures in Canada and USA, and the rejection of tunnel masses for application as concrete aggregates for the construction of the Follo line tunnel in Norway, have raised questions regarding the test methods and regulations for sulfides and pyrrhotite in concrete aggregates. A Norwegian R&D project led by NTNU is currently looking into the characterization and quantification of sulfide minerals in aggregates (WP1) and working with the development of test methods for documentation of the damage potential in concrete (WP2). There is a close collaboration between the Norwegian research team and researchers from the university of Laval in Canada which have been working with pyrrhotite in concrete for over a decade. This paper introduces the basic chemistry of the reactions of pyrrhotite in concrete, presents examples of deterioration caused by pyrrhotite and lists the relevant regulations currently in place in Norway and North America. Eventually, the challenges and research questions raised will be discussed and how we are planning to tackle these will be presented.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.007 |
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".