Investigation of Soil Physicochemical Effects on the Corrosion of Buried Iron Pipes
Bibliographic record
Abstract
Soil corrosivity was an active problem of water pipeline damaged by corrosion that affects the performance of pipe manufacturers. In Addis ababa, groundwater pipelines were facing breakage and like due to corrosion damage of the pipes. The population of nearly four million were facing a shortage of clean and continuous water supply. Maintenace and replacing old pipes with new ones increased additional cost and delay of water supply for the city. For this investigation of corrosion, causes were conducted which soil property is the one factor. Investigation of soil corrosivity for a given specific location before installation is important to design robust pipes that can serve for long life. Soil physicochemical behaviors of the soil parameters were pH, moisture content, and electrical resistivity for any type of soil. In addition, soil bulk density, total nitrogen, soil texture, and electrical conductivity were also the main factors to be studied. The laboratory result indicated that pH of 6.98-7.04, moisture content of 23.7-37.5%, and electrical conductivity of 0.105-313 ds/m were observed. Total nitrogen was small as 0.06-0.10 for a type of soil were class and loam soils. From the analysis of eight soil samples taken from different cities. The results show that the corrosivity behavior of buried iron pipes in the capital city of Ethiopia was moderately corrosive. As confirmed from various soil samples tested from corroded pipes at different depths of 40, 80, and 120 cm. The influence of soil corrosiveness factors initiates pits formation and propagates its width and depth on the surface of pipes.
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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 | 0.001 | 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".