Corrosion Assessment of Reinforced Concrete Made with Secondary Treated Wastewater and Fly Ash, with Sodium Nitrite as a Corrosion Inhibitor
Bibliographic record
Abstract
The corrosion of steel reinforcement in concrete, often caused by carbonation and chloride ingress, poses a significant threat to the durability of reinforced concrete structures.The use of secondary treated wastewater (STW) in concrete has emerged as a sustainable alternative to potable water, though its residual contaminants-such as chlorides and dissolved solids-raise concerns about increased corrosion risk.This study investigates the corrosion behavior of M30grade concrete made with STW, incorporating 10% fly ash as a partial cement replacement and sodium nitrite at 1%, 2%, and 3% (by cement weight) as a corrosion inhibitor.Using the half-cell potentiometer method in accordance with ASTM C876-15, corrosion activity was monitored over 14 months.Concrete specimens with 50 mm and 100 mm cover depths were prepared using STW from three Bangalore treatment plants: Bellandur, Jakkur, and Nagasandra.Results revealed that sodium nitrite, particularly at 1% and 2%, significantly reduced corrosion risk, with half-cell potentials remaining above -200 mV-indicating a low probability of corrosion.A 100 mm cover depth provided better protection than 50 mm.Despite initial corrosion susceptibility due to STW contaminants, the use of fly ash and inhibitors effectively mitigated the risk.By the end of the study, corrosion performance was comparable to concrete made with potable water, supporting STW's feasibility in sustainable construction
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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 | 0.000 | 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 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".