An Efficient Finite Element Formulation for the Analysis of Acoustic and Elastic Waves Propagation in Sound Packages
Bibliographic record
Abstract
A new mixed finite element formulation very well adapted to analyze the propagation of elastic and acoustic waves in porous absorbing media is presented. The proposed new formulation is based on modified Biot's equations [1,2,3] written in terms of the skeleton displacement and the acoustic pressure in the interstitial fluid. It generalizes the previous formulation proposed in reference [11], and has the great advantage over existing formulations [5, 6, 7, 8, 9, 10, 11, 12 and 13] of automatically satisfying interior and exterior boundary conditions without having to compute surface coupling integrals at porous sub-domain interfaces. When elastic forces in the skeleton are neglected, the formulation automatically degenerates to an equivalent fluid model taking into account inertial coupling with the skeleton. In addition it reduces to a minimum the number of degrees of freedom (dofs) and considerably simplify the modeling effort by allowing the computation of the generalized impedance matrix added by complex porous components to the vibro-acoustic impedance matrix of the bare vehicle body. Thus it simplifies the cooperative work between vehicle suppliers and manufacturers. This generalized mixed formulation and associated equivalent fluid model has been implemented by STRACO (France) in RAYON-PEM Solver. It is shown in this paper, that the numerical results predicted with RAYON-PEM agrees very well with experimental results using bazooka impedance tube and RTC tests.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".