Analytical Study of Torsional Wave Behavior in Graded Poroelastic Layer Bonded to Viscoelastic Foundation
Bibliographic record
Abstract
This study presents a theoretical investigation of torsional wave propagation in a graded, fluid-saturated porous layer perfectly bonded to a Kelvin–Voigt viscoelastic half-space. The porous layer exhibits anisotropic behavior with spatially varying rigidity and density, capturing material gradation effects. A complex dispersion relation governing wave propagation is derived using the method of separation of variables, and the real and imaginary components are used to characterize phase velocity and attenuation, respectively. The influence of porosity, gradation, and viscoelastic damping on the dispersion characteristics is examined through numerical analysis. Results indicate that porosity enhances both phase and damping velocities due to fluid–solid coupling, while increasing material gradation leads to stiffer response and stronger attenuation. The model reduces to classical cases under specific parameter limits, providing a basis for validation and comparative assessment. The findings contribute to a deeper understanding of wave dynamics in heterogeneous and dissipative media, with implications for subsurface characterization, seismic analysis, and the design of functionally graded composites.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".