A Finite Element Analysis of the Residual Stresses Incurred During Bending of Pipes
Bibliographic record
Abstract
This work illustrates the potential for finite element methods to be used in support of metal fabrication processes. The focus is an analysis of the residual stresses incurred during cold bending of small diameter pipes. The pipe was modeled using 3D constant strain elements. The mandrels used to support the pipe and apply the necessary bend forces were modeled using 2D rigid surfaces. Contact surfaces were defined on the outside of the pipe and the inside of the mandrels. The fabrication process was simulated by programming the nodes of one of the mandrels with prescribed velocities. The finite element analysis was performed using H3DMAP, proprietary software that includes a hybrid explicit/dynamic relaxation module. The technique is a quasi-static approach that discounts inertial effects. The finite element analyses are used to predict the residual stresses and plastic strain in the pipe. The studies involve a constant pipe size. Two stress/strain curves are used. The effect of using isotropic or kinematic material hardening models, compressive pre-stressing and differing bending procedures are considered, and results compared. The details of each simulation are shown to influence the calculated residual stress field.
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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 | 0.001 | 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".