Comparing the Cavitation and Slurry Erosion Wear Resistance of 16Cr-5Ni Stainless Steel With 13Cr-4Ni CA6NM Stainless Steel
Bibliographic record
Abstract
Abstract In the current work, 16Cr-5Ni stainless martensitic cast steel was evaluated in cavitation and slurry erosion tests under different thermal aging treatments (TATs) using an ultrasonic vibratory cavitation apparatus and an in-house-designed jet slurry tribometer. The steel was homogenized at 1100 °C for 40 h and then thermal ageing was performed at 475 °C, 550 °C, and 625 °C for 4 h. The cavitation test results showed a lower wear-rate was obtained under TAT at 475 °C, followed by TAT at 550 °C, and a higher wear-rate was found under TAT at 625 °C. A good correlation was established between hardness and the maximum erosion rate in the cavitation results. In the slurry tests, the jet stream contained a fixed mass fraction of 1.25 wt% sand. The evaluated impingement angles were 45 deg and 90 deg, and better performance was obtained under TAT at 475 °C and TAT at 550 °C. The results for the thermal aging of 16Cr-5Ni were compared with those of traditional CA6NM (13Cr-4Ni) steel, which is widely used in the manufacturing of turbine runners. Under every condition evaluated, 16Cr-5Ni presented a cavitation erosion resistance value higher than that of CA6NM, and the slurry erosion resistance of both steels was very similar when 16Cr-5Ni under TAT at 475 °C or 550 °C was compared with CA6NM. Therefore, 16Cr-5Ni stainless martensitic cast steel could be another alternative to the promising results obtained for the manufacturing of turbine runners.
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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".