Effect of the Specific Heat Ratio on the Aerodynamic Performance of Turbomachinery
Bibliographic record
Abstract
Many gases, including carbon dioxide and argon, have been considered as alternative working fluids to air in a number of design studies for closed and semi-closed gas turbine engines. In many of these studies, it has been assumed that if the gas constant R and specific heat ratio γ are included in the speed and flow parameters, the compressor map or turbine characteristic is applicable to other working fluids. However, similarity arguments show that the isentropic exponent itself is a criterion of similarity and that the turbomachinery characteristics, even when appropriately nondimensionalized, will, in principle, vary as the γ of the working fluid varies. This paper examines the effect of γ on turbomachinery characteristics, mainly in terms of compressors. The performance of a centrifugal compressor stage was measured using air (γ=1.4), CO2(γ=1.29), and argon (γ=1.67). For the same values of the nondimensional speed, the pressure ratio, efficiency, and choking mass flow were found to be significantly different for the three test gases. The experimental results have been found to be consistent with a CFD analysis of the impeller. Finally, it is shown that the changes in performance can be predicted reasonably well with simple arguments based mainly on one-dimensional isentropic flow. These arguments form the basis for correction procedures that can be used to project compressor characteristics measured for one value of γ to those for a gas with a different value.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".