Seismic Response of Pipelines from Multi-Point Shaking Table Tests
Bibliographic record
Abstract
Buried pipelines are an essential underground infrastructure of modern societies, which is susceptible to damage during earthquake events. The characteristics of seismic excitation that impact pipelines are affected by the spatial distribution of seismic waves and the large extent of long pipelines. A shaking table testing program was conducted on scaled buried pipeline model to investigate its seismic response under non-uniform ground motion. The pipelines-sand model was enclosed in a suspension continuum soil box excited using three shaking tables that can induce uniform and non-uniform seismic excitations. The soil bed was uniform dry sand and the model pipeline was 6.0 m in length and 150 mm in diameter. The soil was instrumented with accelerometers along the soil profile, while the pipeline was instrumented with strain gauges and accelerometers around the pipeline. The soil-pipeline model was subjected to twenty-four different ground motions. The recorded data from all instrumentation were analyzed to evaluate the influence of non-uniform seismic excitation on the pipeline response. The results demonstrated that the pipeline response to longitudinal acceleration was larger than the response of surrounding soil under non-uniform excitation. In addition, the peak pipeline tensile and compressive strains to non-uniform ground motion was about twice that under uniform ground motion.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".