Large-Scale Modeling of Preshaking Effect on Liquefaction Resistance, Shear Wave Velocity, and CPT Tip Resistance of Clean Sand
Bibliographic record
Abstract
The effect of preshaking and repeated liquefaction on liquefaction resistance was studied in a large-scale shaking table experiment, in which a sequence of 51 shakings was applied to the base of a 5-m uniform deposit of saturated clean Ottawa sand. Three event types were used in a very intense repeated pattern: mild preshaking Events A, stronger preshaking Events B, and extensive liquefaction Events C, with each Event C typically liquefying most or all of the deposit. Relative density, cone penetration test (CPT) tip resistance, and liquefaction resistance to Events A and B were found to increase significantly throughout the 51-shaking sequence, with the shear wave velocity (Vs) increasing slightly. However, the CPT tip resistance and liquefaction resistance decreased temporarily after each Event C, recovering rapidly with additional preshaking—presumably due to a decrease and subsequent increase in the soil lateral stresses. The results for the different shakings were compared with available CPT- and Vs-based field liquefaction charts, with and without accounting for the fact that the soil deposit was much younger than the case histories covered by the charts (age factor). The liquefaction response for Events A, B, and C was reasonably well predicted by the CPT chart when the age factor was considered, including Events A immediately after liquefaction by an Event C. The implications of the research were discussed for the geologic age, preshaking and liquefaction effects observed in the field, including reliquefaction response of the same site by milder aftershocks after the main earthquake shock.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".