Comparison of Transient Modeling Techniques for a Micro Turbine Engine
Bibliographic record
Abstract
A large number of papers have been published on transient modeling of large industrial and military gas turbines. Few, however, have examined micro turbines. The decrease in size affects the relative rates of change of shaft speed, gas dynamics and heat soak. This paper compares the modeled transient effects of a micro turbojet engine comprised of a single stage of radial compression and a single stage of axial expansion, with a diameter of 12cm. The model was validated with experimental data. Several forms of the model were produced starting with the shaft and fuel transients. Conservation of mass, and then energy, was subsequently added for the compressor, combustor and turbine, and a large inlet plenum that was part of the experimental apparatus. Heat soak to the engine body was incorporated into both the shaft and energy models. Heat soak was considered in the compressor, combustor and turbine. Since the engine diameter appears in the differential equations to different powers, the relative rates of change vary with diameter. The rate of change of shaft speed is very strongly influenced. The responses of the different transient effects are compared. The relative solution times are also discussed, since the relative size of the required time steps changes when compared to a large engine.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".