Thermal and residual stress distributions in butt fusion joints of HDPE pipes: FE simulation and experimental validation
Bibliographic record
Abstract
Butt fusion welding is widely applied for connecting high density polyethylene (HDPE) pipes but may generate residual stresses in the welded joints, interfering the bearing capacity and the service life of the pipeline system. As a result, tensile tests of the weld joints and the base HDPE specimens have been performed for investigating the effects of welding parameters on the mechanical properties of the two types of specimens. In addition, the hoop residual stresses in the base material and weldments are measured through open ring method and blind-hole method respectively. The finite element (FE) model taking temperature-displacement coupling into consideration has been established based on elastoplastic constitutive equations to depict the residual stress distribution during the welding process. The results show that the maximum tensile yield strength of the welded joints can be achieved when the heating temperature is 230°C, heating time is 100s and welding pressure is 2.5MPa. The residual stress of the base material is tensile at the inner surface while it is compressive at the outer surface. The FE simulation reveals that the residual hoop stress at both the inner and outer wall of the pipe is maximized near the welding seam and manifests itself as tensile stress. Following the path of welding seam-heat affected zone-base material the residual stress first decreases to negative and then increases to remain steady as tensile stress and compressive for inner wall and outer wall respectively. Furthermore, the increase of heating temperature and heating time will increase the residual stress value.
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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 | 0.001 |
| 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".