Investigation of Noise Sources in Turbulent Hot Jets Using Large Eddy Simulation Data
Bibliographic record
Abstract
Through the use of Lighthill’s acoustic analogy, the aim of this paper is to investigate the noise sources of turbulent heated round jets using previously simulated Large Eddy Simulation (LES) data. Two heated and one unheated jet are considered to study the e ects of heating on the noise source contributions to the far-field. Firstly, the computed overall sound pressure level (OASPL) and spectra are in good agreement with the prediction obtained from the porous Ffowcs Williams-Hawkings (FWH) surface integral method. Like the FWH prediction, however, the computed OASPL over-predicts the experiments by approximately 3dB but the trends agree reasonably well with the experimental results. Through decomposition of the Lighthill source term we obtain such sources as shear, self and entropy noise. An important finding is that when a high speed subsonic compressible jet is heated while keeping the ambient jet Mach number constant, significant cancellations occur in the far-field between the shear and entropy noise. In addition, heating a jet reduces the intensity of the nonlinear self noise terms compared to an unheated jet. For a low speed heated jet, the main contributing source is the entropy noise source while the shear and self noise sources hardly contribute to the far-field noise.
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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 | 0.002 | 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".