RESEARCH OF HIGH TEMPERATURE GAS CORROSION OF LOW-ALLOY CHROME-SILICON CAST IRON IN AN ENVIRONMENT OF ANODIC GASES OF ALUMINUM ELECTROLYSERS
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Bibliographic record
Abstract
The atmosphere of the anode gases of the aluminum electrolyzers of EcoSoderberg contains fluorine compounds, sulfur oxides and vanadium, causing intense gas corrosion of the elements of the gas collecting bell. Corrosion of cast-iron sections of the gas collecting bell leads to a reduction in their service life, as a consequence of the need for more frequent repairs and is the reason for a decrease in the grade of primary aluminum by iron impurities. The corrosion resistance of low-alloyed chromium-siliceous cast iron (silicon content 3.06 %, chromium 0.71 %) in the anode gases of aluminum electrolyzers was studied. The research was carried out in industrial conditions. Full-profile sections of the gas collecting bell are made of experimental cast iron. The duration of operation of the sections was 24.32 months. The mass loss due to corrosion was 13.5 %, and the average specific mass loss was 0.128 ·10–3, g/(cm2·h). The specific mass loss of routinely used high-strength cast iron with spherical graphite grade HF 50 is almost 4.8 times higher and amounts to 0.614 · 10–3, g / (cm2 · h). The basis of experimental low-alloyed chromium-silicon cast iron is ferritic, graphite secretions have a shape close to spherical, corrosion processes develop along the boundaries of ferrite grains. The hardness of cast iron is 140 – 149 NV. The increased corrosion resistance of cast iron is based on the ability of chromium and silicon to form protective films on the metal surface that prevent the diffusion of oxidizing gases. In particular, silicon contributes to an increase in the point of formation and stable existence in the corrosion products of the lustite phase of FeO up to 900 °C and forms a layer of Fe2SiO4 · SiO2 with increased protective properties and slowing down the processes of high-temperature gas corrosion. The experimental composition of cast iron is recommended for industrial use.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it