Failure assessment of seam-welded pipe under fatigue and thermal loading
Bibliographic record
Abstract
• This paper presents an assessment of the failure of a seam-welded pipeline under fatigue and thermal loading. • Both experimental analysis and numerical simulations utilizing the finite element method (FEM) were conducted to understand potential failure modes of a seam-welded SS304L pipeline. • The experimental analysis explored different aspects of failure, such as stress corrosion cracking, welding defects, and the impacts of thermal and fatigue loading, as well as overloads. • The numerical simulations investigated weld defects, residual stresses, fatigue and thermal loading, and the propagation of fatigue cracks. • It is concluded that the primary cause of failure was linked to suboptimal welding procedures and post-welding treatment, along with the presence of high levels of residual stresses in the heat-affected zone (HAZ) of the weld. This paper presents an assessment of the failure of a seam-welded pipeline under fatigue and thermal loading. The investigation concentrated on analyzing several factors potentially influencing pipeline failure. Both experimental analysis and numerical simulations utilizing the finite element method (FEM) were conducted to understand potential failure modes of a seam-welded SS304L pipeline. The experimental and FEA analyses investigated various failure factors including weld defects, fatigue and thermal loading, residual stresses, and overloads. The study concludes that substandard welding procedures and inadequate post-weld treatment, coupled with elevated residual stresses in the heat-affected zone (HAZ) of the weld, were the primary contributors to failure. The paper systematically outlines the utilization of experimental and FE analyses in examining practical engineering failure instances. This approach strengthens the ability to avert failures and navigate risks with precision. Furthermore, the results highlight the critical significance of adhering to code and standard guidelines concerning pipe seam welds and post-weld treatment practices.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".