Stress analysis of rotating functionally graded polar orthotropic disk under thermomechanical loading
Bibliographic record
Abstract
In this paper, thermo-elastic stress analysis of rotating variable thickness annular disk made of polar orthotropic functionally graded material (FGM) is presented. Elasticity modulus, density and thick-ness of the disk are assumed to vary radially according to a power law function. The material of the disk is assumed to be temperature dependent and different temperature distributions are assumed for variation of the temperature in radial direction. Radial stress and radial deformation of the disk with Clamped- Free (C-F) and Free-Free (F-F) boundary conditions are obtained using the numerical finite difference (FD) method. It is concluded that, by increasing the temperature variation, the radial stress and displacement increase. It is also observed that the radial stress in the rotating FG disk is more than the radial stress in rotating homogeneous disk and by increasing the FG index, the location of maximum stress in the disk shifts toward the outer surface. Also, the effects of temperature variation along the radius and orthotropy of the material on the radial stress and deformation are evaluated and concluded that their effect are significant. The results are compared with the available results in the literature and the good agreement between the present results and results in the literature shows the accuracy of FD method in thermo-elastic analysis of rotating FG orthotropic disk of variable thickness.
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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 | 0.000 | 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 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".