Numerical Prediction of Far-Field Combustion Noise from Aeronautical Engines
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A hybrid methodology combining a detailed Large Eddy Simulation of a combustion chamber sector, an analytical propagation model of the extracted acoustic and entropy waves at the combustor exit through the turbine stages, and a far-field acoustic propagation through a variable exhaust temperature field was shown to predict far-field combustion noise from helicopter and aircraft propulsion systems accurately for the first time. For the single-stream turboshaft engine, the validation was achieved from engine core to the turbine exit. Propagation to the far field was then performed through a modeled axisymmetric jet. Its temperature modified the acoustic propagation of combustion noise significantly and a simple analytical model based on the Snell–Descarte law was shown to predict the directivity for axisymmetric single jet exhaust accurately. Good agreement with measured far-field spectra for all turboshaft-engine regimes below 2 kHz stresses that combustion noise is most likely the dominant noise source at low frequencies in such engines. For the more complex dual-stream turbofan engine, two regime computations showed that direct noise is mostly generated by the unsteady flame dynamics and the indirect combustion noise by the temperature stratification induced by the dilution holes in the combustion chamber, as found previously in the turboshaft case. However, in the turboengine, direct noise was found dominant at the combustor exit for the low power case and equivalent contributions of both combustion noise sources for the high power case. The propagation to the far-field was achieved through the temperature field provided by a Reynolds-Averaged Navier–Stokes simulation. Good agreement with measured spectra was also found at low frequencies for the low power turboengine case. At high power, however, turboengine jet noise overcomes combustion noise at low frequencies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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