Optimization of a Steam Turbine Blade’s Double-T Root Through Contact Surface Convexity
Bibliographic record
Abstract
The turbine blade is one of the most critical components of a steam turbine. The high thermal loads and large centrifugal forces cause extreme stresses on the blade, especially on its root. This paper focuses on improving the double-T root of a turbine blade of the control stage by decreasing the root’s peak equivalent von-Mises stress. An 18% reduction was achieved in the peak stress by changing the convexity of the contact surface between the root and the groove. The equivalent von-Mises stress was determined in a static structural analysis of a three dimensional finite element model (3D FEM-model) using ANSYS Workbench. This numerical model was developed to include one blade and the associated part of the shaft, whereas the complete circle of blades was considered by applying cyclic symmetry. Furthermore, this paper includes a modal analysis comparing the natural frequencies of the initial FEM-model with the frequencies of the optimized one. The results were established by an investigation of the influence of the FEM-model’s parameters, its material properties, thermal effects, and an additional damping wire in the shroud.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".