Off-Design Performance Comparison Between Single and Two-Shaft Engines Part 1—Fixed Geometry
Bibliographic record
Abstract
Abstract This paper describes an investigation into the off-design performance comparison of single and two-shaft gas turbine engines. A question that has been asked for a long time is which gas turbine delivers a better thermal efficiency at part load. The authors, notwithstanding their intensive searches, were unable to find a comprehensive answer to this question. A detailed investigation was carried out using a state-of-the-art performance evaluation method and the answer was found to be: It depends! In this work, the performance of two engine configurations is assessed. In the first one, the single-shaft gas turbine operates at constant shaft rotational speed. Thus, the shape of the compressor map rotational speed line will have an important influence on the performance of the engine. To explore the implications of the shape of the speed line, two single-shaft cases are examined. The first case is when the speed line is curved and as the compressor pressure ratio falls, the nondimensional mass flow increases. The second case is when the speed line is vertical and as the compressor pressure ratio falls, the nondimensional mass flow remains constant. In the second configuration, the two-shaft engine, the two shafts can be controlled to operate at different rotational speeds and also varying relationships between the rotational speeds. The part-load operation is characterized by a reduction in the gas generator rotational speed. The tool, which was used in this study, is a 0-D whole engine simulation tool, named Turbomatch. It was developed at Cranfield and it is based on mass and energy balance, carried out through an iterative method, which is based on component maps. These generic, experimentally derived maps are scaled to match the design point of a particular engine before an off-design calculation is performed. The code has been validated against experimental data elsewhere, it has been used extensively for academic purposes and the research activities that have taken place at Cranfield University. For an ideal cycle, the single-shaft engine was found to be a clear winner in terms of part-load thermal efficiency. However, this picture changed when realistic component maps were utilized. The basic cycle and the shape of component maps had a profound influence on the outcome. The authors explored the influence of speed line shapes, levels of component efficiencies, and the variation of these component efficiencies within the operating range. This paper describes how each one of these factors, individually, influences the outcome.
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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".