Chemo-Mechanical Effect in Erosion-Corrosion Process of Carbon Steel
Bibliographic record
Abstract
Abstract In this work, the chemo-mechanical effect in slurry-erosion was investigated and an attempt was made to understand the mechanism of the corrosion-enhanced erosion. The chemo-mechanical effect was evaluated with the hardness degradation due to the presence of anodic current on the surface. The micro-hardness measurements of A1045 steel was determined in de-ionized water and in an aqueous solution of 1M NaHCO3 while anodic current was applied. The results showed that the hardness decreased with increasing anodic current density and the relative hardness degradation (ΔHv / ΔHv0) is a linear function of the logarithm of the anodic current density. The dependence of hardness drop on the anodic current density is almost independent of the corrosive media although the carbon steels displayed different polarization behavior in the test solutions used in the current experiments. The erosion and erosion-corrosion tests were conducted with A1045 steel in a slurry comprising 0.1M Na2SO4 aqueous solution + 30% sand under condition of cathodic protection or action of constant applied anodic current, respectively, and the steel was annealed at different temperatures to achieve different hardness. The degradation of mechanical erosion resistance with decreasing hardness implied that a synergistic mechanism would result from the chemo-mechanical effect. It was confirmed again by the test results. The material loss rate due to the corrosion-enhanced erosion increased with increasing applied anodic current density.
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 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".