Effect of composition and microstructure on the rusting of MS rebars and ultimately their impact on mechanical behavior
Bibliographic record
Abstract
Rebar steel is used for reinforcement to aid concrete because concrete does not sustain tension. Thermomechanical treatment is an advanced manufacturing technique for rebar production, but rusting problems emerged in the local steel industry. Raw material sampling included ingot casting (IC) and continuous casting (CC). IC samples corroded more frequently than CC samples. Spectroscopy indicated a small amount of chromium and an improper ratio of manganese to sulfur in IC samples. The improper ratio of manganese to sulfur in IC samples promoted hot cracking at grain boundaries, which resulted in intergranular corrosion. The microstructural results of G40 (air cooled) and G60 (water cooled) showed ferrite and martensite in different proportions. The deformed ferrite in G60 indicated inclination to corrosion, and no proper stable layer of martensite was found. The percentage of martensite was not enough to retaliate against intergranular corrosion. Highly pressurized water initiated pitting corrosion due to the formation of small pits on the surface. Tensile testing revealed 10% reduction in ultimate strength, 8% reduction in yield strength, and 30% reduction in percentage of elongation of corroded samples. Environmental study revealed that the humidity level in the industry was greater than in the laboratory space. High values of SO x and NO x emission revealed the involvement of the environment in the deterioration of the product surface.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".