Dynamic micromechanical model for smart composite and reinforced shells
Bibliographic record
Abstract
Abstract A dynamic micromechanical model based on the asymptotic homogenization pertaining to smart composite and reinforced shells with piezoelectric and piezomagnetic constituents is developed in this paper. Central to the work is the recovery of the so‐called unit cell problems which allow the calculation of the effective coefficients. In turn, these are substituted into the governing equations to obtain a set of basic macroscopic variables which eventually yield asymptotic expansions of all field variables (mechanical stress, electric and magnetic displacement, heat flux etc.). Highlights of the presented dynamic model include the following: (1) the effective properties of the homogenized structure depend strongly on the curvature of the middle surface of the shell; (2) the effective properties are also temporal functions and not merely spatial ones as predicted by other models; (3) the effective properties reflect the influence of all involved constituent material parameters; and (4) the model captures not only the common product properties (magnetoelectricity, pyroelectricity, pyromagnetism) but also other ones relating current density to mechanical displacement, magnetic field, and temperature. These features essentially mean that the homogenized shell is characterized by inhomogeneity or quasi‐homogeneity after the homogenization process and also exhibits memory effect reminiscent of viscoelastic structures. If electrical conductivity is ignored and the effective properties are averaged over the entire time spectrum the results of the model converge to those of previously published quasi‐static models. If, as well, the electrical and magnetic effects are also suppressed the results of the model converge to those of the classical composite shell model.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".