An Engineering Approach for Design and Analysis of Metallic Pipe Joints Under Torsion by the Finite Element Method
Bibliographic record
Abstract
Design and stress analysis of pipe joints are still matters of controversy with respect to a unified design approach, despite the fact that many exact and finite element solutions have been presented in the literature. Owing to the complicated and lengthy nature of most exact solutions, development of an applied method for optimized design and stress analysis of a strong and low-cost joint remains a pressing issue. In this work, a simple method was developed for assessing the behaviour of adhesively bonded tubular joints under torsion, based on a parametric study conducted by ABAQUS finite element software. Many case studies of typical metallic joints under torsion were considered for examining the interactions among the main parameters governing the joint performance (i.e. adhesive thickness, pipe and coupling thickness/diameter, joint length, and material properties). Finally, a prototypical joint was designed by using the developed design curves, and the stress distributions were verified by the same software.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".