Effect of Acidic Rain-Water on Selected Galvanized Aluminium Roofing Sheets
Bibliographic record
Abstract
Nigeria's climatic conditions-characterized by high humidity, substantial rainfall (especially in coastal and tropical regions), and prolonged solar exposure-accelerate the corrosion of roofing materials.This undermines the sustainability of infrastructure by reducing service life, leading to structural degradation and heightened vulnerability to leaks.Compromised roofing systems can facilitate water infiltration and mold growth, posing significant risks to human health and general well-being, and emphasizing the need for climate-resilient building solutions.This research was conducted on selected galvanized aluminum roofing sheets obtained from the open market in Nigeria.The samples were cut to a small size (25mm by 25mm) and immersed in Rainwater, Hydrochloric acid solution (HCl), Sodium chloride solution (NaCl) sulfuric acid (H2SO4).The experiment was performed over 1080 hours, and weight loss measurements were carried out for each sample.In a Hydrochloric acid (HCl) solution, weight-loss experiments.It is predicted that the imported roofing sheet 2(IMS2) and sonic roofing sheet (SNL) are more resistant to Rainwater and hydrochloric acid environments, with the lowest corrosive rate of 0.8g, and thus more stable.While in Sulphuric (H2SO4) environments, Sonic roofing sheet is more resistant and more suitable with a lower corrosion rate of 0.9g.In Sodium chloride (NaCl) environments, imported roofing sheet 2 (IMS2) is recommended, with a lower corrosion rate of 0.5g, and thus more suitable and stable.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".