Pressure Loss Modeling of Non-Symmetric Gas Turbine Exhaust Ducts Using CFD
Bibliographic record
Abstract
In typical gas turbine applications, combustion gases that are discharged from the turbine are exhausted into the atmosphere in a direction that is sometimes different from that of the inlet. In such cases, the design of efficient exhaust ducts is a challenging task particularly when the exhaust gases are also swirling. A parametric Computational Fluid Dynamics (CFD) based study was carried out on non-symmetric gas turbine exhaust ducts where the effects of geometry and inlet aerodynamic conditions were examined. These exhaust ducts comprise an annular inlet, a flow splitter, an annular to rectangular transition region, and an exhaust stub. The duct geometry, which is a three-dimensional complex one, is approximated with a six-parameter model (four geometric and two aerodynamic), which was coupled with a design of experiment method to generate a relatively small number of exhaust ducts. The flow in these ducts was simulated using CFD for different values of inlet swirl and aerodynamic blockage and the numerical results were reviewed so as to assess the effects of the geometric and aerodynamic parameters on the total pressure loss in the exhaust duct. These flow simulations were used as a data base to generate a total pressure loss model that designers can use as a tool to build more efficient non-symmetric gas turbine exhaust ducts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".