Time-Domain Simulation of Nonlinear Acoustic Propagation in a Lined Duct
Bibliographic record
Abstract
The nonlinear behavior of finite amplitude acoustic waves, such as attenuation through shocks and energy transfer between frequencies, are important considerations in the prediction of the inlet fan noise. In this study, a time-domain nonlinear acoustic propagation code with an impedance boundary condition representing the acoustic liners is presented. The full Euler equations are utilized as a model equation for nonlinear wave propagation. Spatial discretization of the equations is accomplished using a high-order conservative scheme on a cell-centered finite volume grid. A time-domain impedance boundary condition is implemented based on a characteristic boundary approach, which is equivalent to the use of a reflection relation in the linear case. The order of accuracy of the broadband impedance model using the z-transform is improved over previous implementations. The NASA Langley grazing impedance tube configuration with a ceramic tubular (CT) liner is adopted for the nonlinear simulation of a lined duct. For the nonlinear simulations, impedance nonlinearity is ignored and only propagation nonlinearity is considered. Simulations of nonlinear propagation for two types of source waveforms are conducted. For saw-tooth wave sources, the energy transfer between the harmonic components is clearly observed during the propagation in the lined duct. For sinusoidal sources at 1 kHz, the attenuation rate by the acoustic liner at the fundamental frequency is the same regardless of source amplitude. Nonlinearity of the liner is discussed by comparison with experimental data.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".