Electro-Mechanical Behavior of Smart Sandwich Plates With Porous Core and Graphene-Reinforced Nanocomposite Layers
Bibliographic record
Abstract
Abstract The use of piezoelectric sensor and/or actuator layers in engineering structures provides smart sandwich structures with adaptive responses. Moreover, due to the brittle behavior of piezoceramic materials, inserting nanocomposite and porous layers between piezoelectric layers offers more flexible and lighter structures along with maintaining the advantages of nanocomposite materials. Therefore, in this paper, we have proposed smart sandwich plates consisting of a porous polymeric core and two graphene-reinforced composite (GRC) layers integrated with two piezoceramic layers. The distributions of porosities and randomly oriented graphene particles are assumed to be functionally graded (FG) along the thickness of core and nanocomposite layers, respectively. For the static behavior of the proposed sandwich plates, the coupled electro-mechanical governing equation has been extracted by minimizing potential energy equation with respect to displacement and electrical potential. The governing equation has been discretized by adopting a higher order shear deformation theory (HSDT) of plates and a developed mesh-free method. Using the developed solution framework, the effects of porosity and graphene characteristics, electromechanical loads, and layer thicknesses on the deflection behavior of the proposed FG piezoelectric porous nanocomposite sandwich plates (FG-PPNSPs) have been studied.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".