Aerodynamic Parametrization of Last Stage Steam Turbine Blades
Bibliographic record
Abstract
Abstract The present paper introduces a novel method to parametrize blade profiles of last stage steam turbines with aerodynamic data. This offers the possibility to specifically influence the flow in order to reduce thermodynamic relaxation losses without changing the desired expansion and redirection of the flow from the ini-tal blade profile. The idea is that the flow channel between two adjacent blades can be regarded as a bent nozzle and the nozzle contour is calculated using aerodynamic data. This nozzle is bent over an ideal streamline, which represents the desired flow redirection, and completed with leading and trailing edges to form a blade profile. In the presented parametrization, the expansion rate is used as variable to adapt the blade profile, as it has a direct influence on condensation and thus thermodynamic relaxation losses. In addition to the distribution of the expansion rate and static pressure along the streamline, the coordinates of the streamline, the total pressure and total enthalpy at the inlet of the profile as well as the distance of the throat are necessary to describe the blade geometry. The new aerodynamic parametrization is capable of accurately representing a Laval-nozzle and a stator cascade. With adapting expansion rates, wetness losses are reduced by 3.5 % for the nozzle and by 2 % for the blade profile.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".