Improving the Efficiency of Sealing Parts for Hollow Body Network
Bibliographic record
Abstract
<div class="htmlview paragraph">Nowadays, expanding sealing parts in automotive hollow body networks are widely used. These parts are usually made up from expanding foams or an assembly of expanding foams and solid materials. The use of these sealing parts has demonstrated an influence on the noise inside the car. These findings proved the necessity of designing sealing parts especially to reduce the propagation of sound through the frame cavities and hollow bodies. In this work, experimental investigations have been conducted to characterize the acoustic performances (absorption, transmission loss) of the individual materials constituting the parts and their assembly. Some design rules have been extracted to improve their efficiencies. Also, to better understand the acoustic behavior of the expanding foams, existing theoretical models for closed or open foams have been tested and compared to measurements. The comparisons showed the importance of accounting for the resonant and non-resonant surface absorption of these closed-cell foams. A simplified modeling of the expanding foam consisting of an elastic core surrounded by a resistive layer is proposed and compared to measurements.</div>
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".