Multi-Disciplinary Design Tool for Axial Flow Turbines
Bibliographic record
Abstract
A preliminary design tool has been created to aid in the design of axial flow turbines. The design tool outputs all of the required geometry and flow conditions for the preliminary design of a single stage axial turbine. Inherent to the tool is its ability to produce performance estimates, both aerodynamically and structurally. The aerodynamic analysis is largely empirical based and makes use of the most up-to-date correlations available in the literature. The tool has been created to obtain a fast estimate of performance and a fast screening of various design variables. The design tool is also required in order to produce a geometrical input for more advanced computational fluid dynamic (CFD) and finite element method (FEM) analyses. A test case has been conducted through the design and development of two single stage turbines for a 1-MW gas turbine engine. The results of the design tool were then compared to those results obtained from extensive CFD and FEM analyses to validate the accuracy of the tool. Overall, the results showed excellent agreement both aerodynamically and structurally.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.047 | 0.011 |
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".