Predictions of Residual Stresses and Deformations in Pipe Bends Produced Using Cold, Warm and Induction Bending Processes
Bibliographic record
Abstract
Cold bending, warm bending (bending with local heating) and induction bending are three manufacturing processes widely used to produce pipe bends. The cold and warm bending processes have been used for the fabrication of carbon steel feeder bends for CANDU® reactors, and the induction bending process was considered for the fabrication of stainless steel feeder pipes for an advanced CANDU reactor. Bending processes result in plastic deformation, and inevitably, introduce residual stresses in the deformed pipes. Residual stresses in feeder bends are believed to be a very important contributing factor in feeder cracking. Different bending processes result in widely different residual stress patterns and magnitudes in pipe bends. Hence, it is important to understand the effect of bending processes and the process parameters used on the residual stress distribution in the bent pipes. Numerical models have been successfully developed to predict the residual stresses and the deformed shapes induced by cold, warm and induction bending processes. This paper provides a comprehensive review of the predicted residual stress distributions, ovality and wall-thickness variations of the cold, warm and induction bends. The predicted results were compared to earlier measurements of spare CANDU feeder bends and test bends. Advantages and disadvantages of the three bending processes are summarized. Numerical approaches for the modeling of residual stresses could be of benefit to engineering estimates of residual stresses in feeder pipes for safety evaluation of nuclear reactors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".