Corrosion Behavior of Thermal Seamless Carbon Steel Boiler Pipes
Bibliographic record
Abstract
The current study was absorbed on corrosion of ASTM A106 grade B -02 seamless carbon steel boiler pipes. Beyond corrosion experiments in corrosive medium with varying pH values, the weight lost in addition to corrosion rate (m.p.y) values were computed. The weight loss of boiler tube specimens exposed to corrosive liquid was shown to rise as the exposure period of the specimens increased. The results of the microstructure imaging showed that a de-carburized film of 240 µm thickness was shaped on the fireside of the pipe boiler, with ferrite and a few phases of pearlite. On the water lateral side, it was revealed that boiler pipe failure begins with small rust particles that expand to greater sizes and form scales that are displaced from the boiler pipe's surface. On the surfaces of the boiler pipe water side, several pits with crevice corrosion were observed. The corrosion amounts were discovered to decrease when the specimens' exposure time to corrosive environments and hydrogen ion concentration contents increased (pH). The findings of mechanical characteristic values such as hardness, yield strength, and tensile strength revealed that the waterside had higher values than the fireside, while the middle of the pipe had reasonable values. The findings also demonstrated that at low pH values, a tiny size of rust was created on the boiler tube specimen surface. However, at high pH values of corrosive medium, big sizes of corrosion rust were observed on the specimen surfaces.
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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) | 0.001 | 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".