Effect of Inlet Temperature Non-Uniformity on High-Pressure Turbine Performance
Bibliographic record
Abstract
The temperature of the flow entering a high-pressure turbine stage is inherently non-uniform, as it is produced by several discrete, azimuthally-distributed combustors. In general, however, industrial simulations assume inlet temperature uniformity to simplify the preparation process and reduce computation time. The effects of a non-uniform inlet field on the performance of a commercial, transonic, single-stage, high-pressure, axial turbine with a curved inlet duct have been investigated numerically by performing URANS (Unsteady Reynolds-Averaged Navier-Stokes equations) simulations with the SST (Shear Stress Transport) turbulence model. By adjusting the alignment of the experimentally-based inlet temperature field with respect to the stator vanes, two clocking configurations were generated: an aligned case, in which each hot streak impinged on a vane and a misaligned case, in which each hot streak passed between two vanes. In the aligned configuration, the hot streaks produced higher time-averaged heat load on the vanes and lower heat load on the blades. As the aligned hot streaks impinged on the stator vanes, they also spread spanwise due to the actions of the casing passage vortices and the radial pressure gradient; this resulted in a stream entering the rotor with relatively low temperature variations. The misaligned hot streaks were convected undisturbed past the relatively cool vane section. Relatively high time-averaged enthalpy values were found to occur on the pressure side of the blades in the misaligned configuration. The non-uniformity of the time-averaged enthalpy on the blade surfaces was lower in the aligned configuration. The flow exiting the rotor section was much less non-uniform in the aligned case, but differences in calculated efficiency were not significant.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".