Industrial Trent Combustor—Combustion Noise Characteristics
Why this work is in the frame
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Bibliographic record
Abstract
Thermoacoustic resonance is a difficult technical problem that is experienced by almost all lean-premixed combustors. The Industrial Trent combustor is a novel dry-low-emissions (DLE) combustor design, which incorporates three stages of lean premixed fuel injection in series. The three stages in series allow independent control of two stages—the third stage receives the balance of fuel to maintain the desired power level—at all power conditions. Thus, primary zone and secondary zone temperatures can be independently controlled. This paper examines how the flexibility offered by a 3-stage lean premixed combustion system permits the implementation of a successful combustion noise avoidance strategy at all power conditions and at all ambient conditions. This is because at a given engine condition (power level and day temperature) a characteristic “noise map” can be generated on the engine, independently of the engine running condition. The variable distribution of heat release along the length of the combustor provides an effective mechanism to control the amplitude of longitudinal resonance modes of the combustor. This approach has allowed the Industrial Trent combustion engineers to thoroughly “map out” all longitudinal combustor acoustic modes and design a fuel schedule that can navigate around regions of combustor thermoacoustic resonance. Noise mapping results are presented in detail, together with the development of noise prediction methods (frequency and amplitude) that have allowed the noise characteristics of the engine to be established over the entire operating envelope of the engine. [S0742-4795(00)00802-4]
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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 it