Elastic Stress Analysis of Shrink-Fit Thick-wall FGM Cylinders
Bibliographic record
Abstract
This study represents analytical analysis of stress and strain within a functionally graded material (FGM) shrink-fitted assembly, considering variations in inhomogeneity parameters, interference value and geometries. The elasticity modulus is modeled to vary continuously as a power-law function along the radial coordinate of the assembly. Assumptions of plane strain and the von Mises criterion with a constant Poisson's ratio are adopted. Based on, equilibrium equation, Hooke's law, the stress-strain relationship within the assembly, and other mechanical theories, a second-order differential equation is derived. This equation accurately represents the elastic field within a Functionally Graded Material(FGM) assembly. Although similar approach have been utilized in the past to examine stress and displacement in FGM cylinders or spheres subjected to pressure, applying this approach specifically to the shrink fitting of FGM cylinders represents a novel and unexplored area of research. The analysis of results reveals the notable impact of variations in the inhomogeneity parameter n and the assembly's geometry on the stress and strain within the Functionally Graded Material (FGM) assembly. Additionally, the interference value plays a significant role in influencing the residual contact pressure, subsequently affecting the transmissible torque. The findings exhibit a commendable alignment with existing results in the literature. It is demonstrated that the elastic characteristics of the FGM can be effectively controlled by managing the values of the aforementioned parameters. Furthermore, these findings prove highly valuable across diverse engineering and scientific domains, since shrink fitting of Functionally Graded Materials (FGM) holds particular significance in numerous applications, notably in fields such as aerospace and biomedical engineering.
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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 | 0.001 |
| 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) | 0.001 | 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".