Coupled Thermomechanical Analysis of Autofrettaged and Shrink-Fitted Compound Cylindrical Shells
Bibliographic record
Abstract
In this study, different configurations of compound multilayer cylinders subjected to autofrettage and shrink-fit processes and under combined cyclic thermal and pressure loads have been investigated and their fatigue life has been evaluated and compared. Fully coupled thermo-elastic analysis is taken into consideration during the calculation of the temperature profile through the wall thickness. Finite element model for the compound two-layer cylinder has been constructed and then validated with previous work in the literature and experimental work. In the experimental work, the temperature has been measured at different locations through the thickness of a two-layer shrink-fitted cylinder (SFC), subjected to internal quasi-static and dynamic thermal loads. Besides, the hoop strain at the outer surface of the cylinder has been measured for the same thermal loads. Using the developed finite element model, the hoop stress distributions through the thickness of different configurations of the compound cylinder have been calculated under different loading conditions, including internal static pressure, internal cyclic thermal loads, and combination of these loads. The mechanical fatigue life has been calculated using ASME codes due to the internal cyclic pressure. Moreover, the stress intensity factor (SIF) has been calculated for these configurations under cyclic thermal loads or cyclic thermomechanical loads, considering thermal accumulation. The stress intensity factors for different configurations have been compared with the critical SIF which is the fracture toughness of the material. The number of stress cycles required until the SIF reaches the critical SIF has been considered as the fatigue life for each configuration. It has been found that for the cases of cyclic thermal loads and combined cyclic pressure and thermal loads, the shrink-fitting of two layers followed by the autofrettage of the assembly is the best configuration to enhance the fatigue life of the two-layer cylinder.
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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 | 0.001 | 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".