Experimental approach for assessing dissipated excess pore pressure-induced settlement
Bibliographic record
Abstract
Upon dynamic loading, saturated soils lose their strengths and undergo deformations resulting in volumetric-induced settlements that vary according to the excess pore pressure generation and dissipation variations. Traditionally, these settlements have been evaluated using standard charts based on one soil type and its relative density (RD). To assess these settlements, this study established a unique experimental methodology based on two laboratory testings: triaxial simple shear and piezoelectric ring actuator technique. Fifty-seven tests were performed on Ottawa F65 sand under strain-controlled cyclic and post-cyclic conditions. A chart was generated, revealing a relationship between the dissipated energy from cyclic loading and volumetric strain ( εv ), based on the shear wave velocity as a controlling factor. This study was compared with previous studies to verify the compatibility of the proposed approach. Another novelty was revealed by studying εv variation with the dissipated pressure. This variation is presented in a post-seismic chart in which deformations are tracked based on the initial soil state and maximum excess pore pressure generation ratio ( Rumax) at the end of the loading phase. For each RD, the soil is divided between liquefied and non-liquefied states according to a specific Rumax ( Rumax-trigger point). The calculation of the volume compressibility coefficient is proven to serve as a liquefaction-triggering criterion identifying the liquefied state.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".