Determination of C2 Stress Index of Back-to-Back Welded Piping Bends Using Finite Element Method
Bibliographic record
Abstract
In current ASME Boiler and Pressure Vessel Code, the C2 stress index for back-to-back elbows welded together is taken as the product of the C2 index of the elbow and the C2 index of the girth butt weld. In recent years, many finite element analyses studies have been conducted on the elbow C2 index itself which have found that the code C2 value is conservative. The girth butt weld C2 given in the code resulted from analytical studies on transition joint between two straight pipes. While the code considers that the secondary stress due to the weld reinforcement including the effect from the mismatch to be small and practically negligible for a thick pipe, it recommends a formula to calculate C2 for weld in a thin pipe of thickness less than 0.237”. The purpose of this paper is to present an approach that C2 caused by weld mismatch can be determined by finite element analysis. Back-to-back bends are modeled with 2 typical configurations: in-plane and out-of-plane. Parametric studies of linear elastic secondary stresses are carried out to determine the “worst possible” two bend central line mismatch. The stress indices at elbows and weld location are established. It is found that the C2 index based on the code formula is overly conservative for back-to-back welded pipe bends and the multiplication by the C2 index of the weld is not needed.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".