Water droplet erosion of stainless steel steam turbine blades
Bibliographic record
Abstract
Steam turbine blades are highly subjected to water droplet erosion (WDE) caused by high energy impingement of liquid water droplets. However, most of the published research on this wear phenomenon is performed on laboratory test rigs, instead of addressing WDE of actual steam turbine blades. In this work, the progression of erosion on the surface of ex-service low pressure steam turbine blades was investigated using scanning electron microscopy. The erosion appearance and mechanisms are compared with laboratory test rig results that are carried out using a rotating disk rig according to ASTM G73 standard. Initial and advanced erosion stages could be observed on the steam turbine blades. Similar to the WDE rig coupons, initial pits and cracks were preceded by blade surface roughening through the formation of asperities and depressions. In addition, it was also observed that the twist angle of the turbine blade around its diagonal, is an important parameter that influences its WDE. Twist angle has an effect on: impact angle, erosion appearance, impact speed, and the affected area. Furthermore, according to the current experimental results, multi-ray rig erosion test results are considered the closest simulation to the actual ex-service blade in terms of damage appearance.
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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".