SCF and Fatigue Analysis of Sphere-Nozzle Intersections With LTA
Bibliographic record
Abstract
A linear elastic finite element analysis (FEA) is carried out to determine the stress concentration factor (SCF) of a pressurized sphere-nozzle intersection. Nine-noded axi-symmetric 2D (ring) elements are used, and vessels without and with inner-wall local thinned areas (LTA) are considered. The SCF values obtained for vessels with uniform wall thickness are compared with previously published experimental and analytical results, and also with results from standard formulas given in the literature. An evaluation is made of the effect on the SCF of three types of inner-wall LTA; thinning in the nozzle, in the sphere, and in both components. As well, an evaluation is made of the effect on the SCF of growth of the LTA away from the intersection. A detailed parametric study is then carried out to determine the SCF for vessels with different depths of LTA. An elastic-plastic fatigue analysis for simulated seismic action is next carried out for some sample intersections, without and with LTA. The results provided are intended to contribute to the information available on the stress and fatigue characteristics of sphere-nozzle intersections with LTA.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".