Effect of Bolt Spacing on the Circumferential Distribution of the Gasket Contact Stress in Bolted Flange Joints
Bibliographic record
Abstract
Abstract Bolted flange joints are part of pressure vessel and piping components and are extensively used in the chemical, petrochemical, and nuclear power industries. They are simple structures and offer the possibility of disassembly, which makes them attractive to connect pressurized equipment and piping. In addition to being prone to leakage, they often require maintenance while in operation in which case the bolts are either retightened as in hot torquing or untightened to be replaced. Although costly shutdowns are avoided, such maintenance work exposes the operator to a potential risk because the bolt load alteration can produce a gasket load unbalance, which results in the local gasket contact stress to drop below some critical value, causing major leak and hence jeopardizing the life of the worker. This paper addresses the issue of the contact stress level unbalance around the flange when the bolts are subjected to initial tightening. The study compares the contact stress distribution variations, an analytical developed model based on the theory of rings on elastic foundation, to those given by the finite element model and the simple beam on elastic foundation model developed by Koves (2007, “Flange Joint Bolt Spacing Requirements,” Proceedings of PVP2007, ASME Pressure Vessel and Piping Division Conference). This study is developed for the purpose of helping limit the degree of load increase in hot torquing or the maximum number of bolts to be replaced at a time and identify those flanges for which the bolt cannot be replaced in service.
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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".