Test Methods For Evaluating The Oxidization Potential Of Sulphide –Bearing Aggregates And Its Effects On Concrete Durability
Bibliographic record
Abstract
This research project focuses on the development and validation of test methods to evaluate the potential oxidation of sulphide-bearing aggregates, which can cause severe damage when used in concrete. The mechanism of damage is believed to consist of two parts: (a) the oxidation of sulphide minerals, which results in the formation of ferric hydroxide, and (b) the formation of sulphuric acid, which reacts with calcium hydroxide in concrete leading to an internal sulphate attack. Both parts produce a volume increase, damaging the concrete. A simple, quick and economical test method was developed and used to test thirty-one aggregates with different sulphur content. This test involves soaking the aggregate in an oxidizing agent at room temperature, washing the aggregate on a specific sieve, and drying it at 80°C. The soaking and drying cycle is repeated and the disintegration of the aggregates is measured as % mass loss. The composition of the oxidizing solution was evaluated, and the assessment of the aggregate was related to the presence of iron and sulphur ions in the solution after the test. The aggregate oxidation test developed here is anticipated to be adopted as a screening test method by North American standards due to its simplicity and applicability to a wide range of aggregates. The expansion of recently developed mortar bar samples containing a limited number of aggregates proves that the test can show expansion in aggregates with sulphide as well as high silica content; however, the high-silica aggregate did not show significant expansion in the second stage of the test, unlike the sulphide-bearing aggregates. The test was examined for its ability to evaluate the effects of supplementary cementing materials (SCM`s) on mitigating the damage in mortars containing sulphide-bearing aggregates. The results revealed that extended exposure to the oxidizing agent caused damage in the bar due to reasons other than the oxidation of sulphide phases when SCM with high reactive alumina is used. In addition, the results revealed that silica fume and low-calcium fly ash were effective in mitigating the damage, however, the efficacy of SCM`s is mainly linked to their ability to reduce the penetration of oxidizing agents into the mortar bars. These results need to be validated using field investigations. Concrete samples were tested under different conditions in an attempt to replicate the damage mechanisms in concrete samples under lab conditions. Some of the testing regimes showed promising results and are recommended for future studies.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".