A combined modeling and experimental investigation of ultrasonic attenuation mechanisms in cancelous bone-mimicking aluminum foams
Bibliographic record
Abstract
Bone is composed of cancelous and cortical bones. Cancelous bone, which is more complicated than cortical bone in terms of structure, is inhomogeneous, anisotropic, and porous. The trabeculae form interconnected network with viscous marrow filling the pores. The presence of trabeculae makes cancelous bone a highly scattering medium. Trabecular bone spacing is considered an important parameter to detect change in bone tissue microstructures. However, due to high porosity and heterogeneity of human cancelous bones, the underlying mechanisms of interactions between ultrasound and cancelous bones are still not fully understood. The water-saturated aluminum foams were previously studied for the suitability of cancelous bone-mimicking phantoms. The ligament thickness and pore size of the foam samples were very similar to those of human cancelous bones. Recently, we performed the micro-scale elastic modeling of broadband ultrasound traveling through the water-saturated aluminum foams using the standard Galerkin finite element method. The simulated results were compared with the experimental measurements using the derived broadband ultrasound attenuation coefficients. The results strongly suggested that wave scattering and mode conversion were the dominant attenuation mechanisms of ultrasound propagating in aluminum foams. The study further demonstrated the capability of the finite element method to effectively simulate the signatures of the ultrasound signals propagating in fluid-filled weakly absorptive porous structures.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".