Asymptotic Homogenization Models for Smart Composite Plates with Rapidly Varying Thickness: Part I-Theory
Bibliographic record
Abstract
Asymptotic homogenization models for smart composite plates with rapidly varying thickness and periodically arranged actuators are derived. The effective elastic, actuation, thermal expansion, and hygroscopic expansion coefficients are obtained. The actuation coefficients characterize the intrinsic transducer nature of active smart materials that can be used to induce strains and stresses in a coordinated fashion. Examples of such actuators employed with smart composite material systems are derived from piezoelectric, magnetostrictive, and some other materials. It is shown that the original problem for the regularly non-homogeneous smart composite plate with rapidly oscillating thickness reduces to a system of eight simpler types of problem. It is precisely these "unit-cell" problems that enable the determination of the aforementioned effective coefficients and subsequently the strain and stress fields. In the limiting case of a thin elastic plate of uniform thickness the derived model is shown to converge to the familiar classical plate model. In Part II of this work, the theory is illustrated by means of examples pertaining to a thin smart laminated plate of uniform thickness and a wafer-type smart composite plate reinforced with smart ribs oriented along the tangential directions of the plate.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".