DYNAMIC RESPONSE OF FUNCTIONALLY GRADED NANOCOMPOSITE BEAMS SUBJECTED TO A MOVING LOAD USING A MESH-FREE METHOD
Bibliographic record
Abstract
In this paper, the dynamic response of functionally graded nanocomposite beams under the action of a moving load are investigated. Three different types of Carbon NanoTubes (CNT’s) distributions in a polymer matrix material are studied; Uniform Distribution (UD), Symmetrically Functionally Graded (SFG) distribution and Unsymmetrically Functionally Graded (USFG) distribution. The analysis is carried out by a mesh-free method using the two-dimensional theory of elasticity. After validation, the effects of different design parameters such as CNT’s distribution, the velocity and position of the moving load on the dynamic behavior of the beam are examined. The results also highlight the importance of the reinforcement distribution type from a design perspective. The current approach can serve as a benchmark against which other semi-analytical and numerical methods based on classical beam theories can be compared.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".