Analytical Modeling of Shrink-Fitted FGM Thick-Walled Cylinder
Bibliographic record
Abstract
One off the most powerful assembly technique is the shrink-fitting process.It is found in many fields such us mechanics, petroleum, military industries as well as in nuclear power plants etc. This article developed an analytical formulation of shrink-fitted Functionally Graded Material axisymmetric thick-walled cylinder based on the linear plane elasticity theory. The stresses and displacement fields in the thick cylindrical shells are calculated using the laws of linear elasticity. The resulting displacements and stresses are analyzed, and particularly the residual contact pressure and her relationship with the interference values. The results show that the variation of the FGM material composition has a clear effect on the fit pressure in the intersection area of the two fitted cylinders. The value of this pressure affects the distribution of radial and tangential stresses in the FGM cylinder walls. Subsequently, we highlighted the influence of the interference value, on the residual contact pressure which increases with the increase of the interference value. The stresses are modeled for a case study using MATLAB software. keywords. shrink-fit, FGM, Interference, residual stress, Elasticity.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".