Assessment of Equivalent Properties for Flat Multilayered Panels
Bibliographic record
Abstract
Within homogenization techniques, an equivalent properties strategy can be utilized to equivalently represent complex structures into simple ones. This work aims to highlight the limitations of three strategies using a single layer flat panel to represent the vibro-acoustics of flat multilayered structures. The presented limitations provide insight into the potential applicability of this strategy in complex heterogeneous structures. Equivalent material properties and equivalent stiffness coefficients are obtained from the dispersion curves of the reference structures and thereafter utilized to build an equivalent simple structure. To demonstrate the accuracy and limitations of the homogenization strategies, three carefully selected flat multilayered structures are presented. The particular effects of asymmetry, orthotropy, soft core and high damping (structural loss factor, η > 0.5) in multilayered structures are addressed. A wave and forced analysis is performed utilizing the General Laminate Model (GLM) and four different vibro-acoustic indicators (total energy, input and radiated power, as well as diffuse field transmission loss) are computed and compared with reference solutions. The comparisons show that, in general, a single layer plate can equivalently represent flat multilayered structures within the studied frequency range ([50 Hz, 5 kHz]). Inaccuracies of the proposed strategies are also discussed, highlighting the challenge of correctly homogenizing structures with soft core and, in particular, high damping.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".