Time-Dependent Field Performance of Steel-Reinforced High-Density Polyethylene Pipes in Soil
Bibliographic record
Abstract
Steel-reinforced high-density polyethylene (SRHDPE) pipe was developed to overcome the disadvantages of steel and high-density polyethylene (HDPE) pipes. In consideration of the long-term serviceability of buried pipes, the time-dependent performance of SRHDPE pipes deserves investigation. In this study, three 8-m (26.2-ft) SRHDPE pipes were installed in a trench in the field with a soil cover thickness of 0.9 m (3 ft). The backfill materials were well-graded aggregate base 3 (AB3) aggregate and poorly-graded crushed stone. A new concept, equivalent pipe stiffness factor, was proposed to consider the large difference in stiffness between pipe and soil for calculating pipe deflection under long-term conditions. The test sections were instrumented with earth pressure cells, displacement transducers, and strain gauges and monitored continuously for 680 days. Measured data indicated that earth pressures increased with time in both AB3 aggregate and crushed stone sections. Vertical arching factor (VAF) increased faster in the crushed stone section than that in the AB3 aggregate section. Pipe deflections in both sections increased with time. The maximum pipe deflections in the AB3 aggregate and crushed stone sections were 0.3% and 0.4% of the pipe diameter at 680 days after installation, respectively. Strains of plastic valley, plastic cover, and steel ribs in both sections were all smaller than the AASHTO limit within 680 days. Finally, empirical relationships were developed for the VAF and the equivalent pipe stiffness factor in order to predict the performance of SRHDPE pipes at a given time.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".