Comparison of Stresses in the Junctions of Shell Structures with Bolted Flange Rings
Bibliographic record
Abstract
Bolted flange joints are favored across a spectrum of pressure vessel applications within diverse industries, owing to their simplicity in installation and operation. However, ensuring their structural integrity and leak-proof performance necessitates careful consideration of both operational conditions and the nature of the connected shell. Yet, the existing ASME BPV Code for flange design lacks inclusion of a leakage criterion or flexibility analysis, hindering accurate assessment of these critical characteristics. This research aims to comprehensively evaluate the integrity and leakage resilience of various shell configurations attached to flange rings. The investigation will scrutinize pivotal factors such as flange rotation and stress distribution at the flange-shell interface, leveraging diverse shell theories across three distinct flange sizes: NPS 26, 48, and 60. Additionally, four prevalent types of shell connections—cylindrical, spherical, dish, and conical—will be juxtaposed. Notably, all shell connections are directly affixed to the raised-face flange ring. To facilitate comparison and validation, these shell connections will be simulated using a versatile finite element program, augmenting the analytical approach. Noteworthy is the incorporation of the gasket's nonlinear behavior in the finite element analysis, a crucial aspect overlooked in the analytical modeling process.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".