Capacity Matching of Aeroderivative Gas Generator With Free Power Turbine—Challenges, Uncertainties, and Opportunities
Bibliographic record
Abstract
Abstract For gas turbines (GTs) with free power turbines (FPTs), the capacity or flow parameter matching is of prime importance. Accurately matched capacity enables the GT to run at its optimum condition. This ensures maximum component efficiencies and optimum shaft speeds within mechanical limits. This paper presents the challenges, uncertainties, and opportunities associated with an accurate matching of a generic two-shaft aeroderivative high pressure (HP)-low pressure (LP) gas generator with the FPT. Additionally, generic performance trends, uncertainty quantification, and results from the verification program are also discussed. These results are necessary to ensure that the final FPT capacity is within the allowable range, and hence, the product meets the performance guarantees. The sensitivity of FPT capacity to various design variables such as the vane throat area, vane trailing edge size, and manufacturing tolerance is presented. In addition, issues that may arise due to not meeting the target capacity are also discussed. To conclude, in addition to design, analysis, and statistical studies, a system-of-systems approach is mandatory to meet the allowed variation in the FPT capacity and hence the desired GT performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".