LIQUEFACTION MITIGATION USING VERTICAL COMPOSITE DRAINS: FULL SCALE TESTING
Bibliographic record
Abstract
This Innovations Deserving Exploratory Analysis (IDEA) project evaluated the behavior of vertical composite earthquake drains under full-scale conditions, employing controlled blasting techniques to liquefy loose sand at a test site in Vancouver, British Columbia. A blast liquefaction test was first performed on an untreated site and then the same explosive charge sequence was used on two sites treated with earthquake drains, one installed with low vibration and the other with high vibration. Although the earthquake drains were insufficient to prevent initial liquefaction during the rapid loading produced by the blasts, the measured rate of dissipation was significantly greater at both drain test areas than in the untreated area. Dissipation rates were similar for both areas treated with drains. Despite the high pore pressures, the blast induced settlement in the first drain test area was only 60% of that in the untreated area. CPT soundings conducted over a two month period after blasting showed a 20 point increase in relative density for the layer where drains were installed with low vibration. This result indicates that both blast treatment and drain installation can produce significant increases in density. With minor modifications in the input parameters, computer analyses performed using FEQDrain were successful in matching measured pore pressure and settlement response during the blasting. These calibrated models were then used to model response to a variety of earthquake events. The results indicate that the drains can prevent liquefaction and excessive settlement when drain diameter and spacing are properly designed for the expected earthquakes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".