Effect of Bolt-Up Stress Level on the Strength of ASME B16.5 and B16.47 Standard Flanges
Bibliographic record
Abstract
Abstract ASME B16.5 and B16.47 flanges are extensively used in the pressure vessels and pipping industry. The origin of their class and size is not based on the amount of initial bolt load they can carry nor the level of tightness they can achieve. Their PV rating does not give an indication on the level of stress they are subject to and little is known on their ability to withstand the bolt stress level they are subjected to during initial bolt-up and under operation. The integrity and leak tightness of ASME B16.5 and B16.47 made of SA105 material needs to be analyzed individually in order to identify the flange classes and sizes that are more vulnerable to initial bolt-up stress level. This paper proposes the use of an accurate analytical model to appropriately address the integrity and tightness of the complex statically indeterminate weld neck standard flange connections based on the flexibility and the elastic interaction between the different joint elements. As such, the most critical standard flanges in terms of class and size will be identified in order to avoid their structural and leakage failure. The model is first tested and validated using simulations using FEM on different sizes of class 900 flanges. The study will investigate the effect of the initial bolt preload on parameters such as flange rotation and stresses in the flange, gaskets and bolts. The most critical size and class flanges and their highly stressed locations will be revealed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".