Results of a Full-Scale Fault-Offset Test on a Glass Fiber Reinforced Polymer Pipe
Bibliographic record
Abstract
Glass fiber reinforced polymer (GFRP) pipe is increasingly being used as a corrosion resistant alternative to steel for distribution pipelines. Since these may be subject to flexural stress caused by ground movement, this study examines the response of GFRP pipe to permanent ground deformation and the failure mechanisms exhibited. A 6 m GFRP pipe segment was buried in dense olivine sand in a moveable split box able to simulate a 90° normal fault line. The segment was buried 1.2 m deep and subjected to fault offset of 120 mm. Point data was gathered at locations of maximum curvature using strain gauges to corroborate continuous fiber optical strain data taken lengthwise along the crown and invert. Fiber data corroborated strain gauge data where they coincided although fibers were ineffective after exceeding 8000 micro strain. Strain data initially showed little sign of material failure in the pipe, but upon further analysis fiber data showed that as fault offset increased, the strain increase between reading intervals increased at the maximum tension point. Immediately after excavation the segment showed little sign of physical damage aside from some residual deformation. Then weeks after excavation the segment recovered its original shape and cracking had become visible around the point of peak curvature.
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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 | 0.000 |
| 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) | 0.001 | 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".