Polynomial relations for quasi-static mechanical characterization of isotropic poroelastic materials
Bibliographic record
Abstract
This paper proposes a quasi-static method for the characterization of the elastic properties of poroelastic materials. The method is based on the development of polynomial relations among compression stiffness, Young’s modulus, Poisson’s ratio, and shape factor derived from high order axisymmetrical finite element simulations on a disk-shaped poroelastic sample under static compression. The shape factor is defined as half the radius to thickness ratio of the sample. The polynomial relations account for the fact that the disk sample “wants” to bulge sideways when compressed between two rigid plates on which it is bonded. A compression test setup is used to measure the compression stiffness of two disk samples of different large shape factors. The measured stiffnesses together with the polynomial relations lead to a system of two equations and two unknowns. The solution of the system yields the Young’s modulus and Poisson’s ratio of the poroelastic material. Employing the proposed quasi-static method, Young’s modulus, Poisson’s ratio, and loss factor are measured for a poroelastic foam. The measured elastic properties are used in the Biot poroelasticity theory to predict the sound absorption coefficient of the foam. The prediction is finally compared with a standing wave tube measurement. A good correlation is obtained.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".