Importance of Inlet Total Pressure Conditions in Evaluating Performance of Non-Symmetric Gas Turbine Exhaust Ducts
Bibliographic record
Abstract
When highly non-symmetric exhaust ducts are installed on a gas turbine engine, the asymmetries result in a non-uniform circumferential total pressure condition at the inlet of the duct. When testing these ducts experimentally or computationally the correct inlet conditions are often not known or cannot be reproduced. To study the sensitivity of duct performance to inlet conditions, an experimental and computational study of a non-symmetric gas turbine exhaust duct that includes a 160° turn with an annular to rectangular transition, has been carried out over a range of inlet conditions. The inlet conditions varied include circumferential total pressure profiles and swirl. The experimental studies have been carried out in cold flow with several non-uniform total pressure inlet conditions. Computational fluid dynamic (CFD) techniques validated against the experimental results, have been used to extend the range of inlet conditions beyond the range that could be obtained experimentally to those typical of an engine installation. Results show that the total pressure inlet conditions have a significant effect on the flow structure in the exhaust duct and that the performance of the exhaust duct degrades as the level of circumferential non-uniformities increase. However, trends in geometric optimization identified experimentally using cold flow and uniform total pressure inlet conditions are confirmed computationally with circumferential non-uniformities typical of actual engine operations. This suggests that although inlet conditions are important for determining the level of performance, the configuration of the optimized geometry is somewhat independent of the inlet conditions.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".