Distributed Strain Measurements on Steel Pipes with Simulated Corrosion Pits Subjected to Four-Point Bending
Bibliographic record
Abstract
Deterioration due to pitting corrosion is one of the main causes of cast iron and steel pipe failure; however, few studies report on how corrosion pit geometry influences the mechanical response of buried pipelines. In this paper, a series of four-point bending tests were used as proxies for buried pipe tests to investigate the strain distributions around simulated corrosion pits. Three corrosion pit geometries were used to investigate the influence of pit geometry on local strain distributions at the invert of the pipe arising from longitudinal bending: (1) a cylindrical perforation all the way through the pipe wall; (2) a cylindrical pit extending partially through the pipe wall and having a flat bottom; and (3) a spherical pit extending partially through the pipe wall. Distributed fiber-optic strain sensors were used to measure the longitudinal strains along the crown, springlines, and invert of the pipe and circumferential strains around the simulated corrosion pits. Different longitudinal strain distributions were observed across the top of these pits on the exterior surface of the pipe and under the pit on the interior surface. The maximum longitudinal tensile strains measured on the two samples with simulated pits that partially penetrated the pipe wall were about 2.5 times higher than an intact specimen. For the circumferential strains, comparisons were made to strains calculated using the Kirsch solution for a flat plate with a circular hole. Although the calculated values of maximum tensile hoop strain were similar to the experimental measurements obtained from the perforated samples, the distributed strain measurements around the pits were different from the calculated distributions. This is because the traverse strains (the strains 90° from the longitudinal direction at the invert of the pipe) near the pit are more compressive than those assumed when imposing uniaxial stress or uniaxial strain conditions in the Kirsch solution; when biaxial strain fields are imposed in the Kirsch theory, as obtained from three-dimensional numerical analyses, the closed-form solution provides effective estimates of stress and strain around perforations. Finally, comparisons were made to strain measurements from a buried pipe subjected to longitudinal bending, and these indicate that four-point bending tests can capture critical peak tensile strains that would lead to failure, but not the full distributed strain profile.
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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) | 0.001 | 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 | 0.000 | 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".