Mechanical model for the analysis of liquefaction of horizontal soil deposits
Bibliographic record
Abstract
During the development of liquefaction in a soil deposit subjected to vibration there are two processes which work in opposite directions. The volume compaction tendency under cyclic loading causes the pore water pressure to rise, and the dissipation of excess pore water pressure (consolidation) decreases it. Recently, Martin, Finn and Seed (l975) studied the mechanics of pore water pressure generation of a soil sample subjected to cyclic loading and a relation between shear strain cycles, volume compaction and pore water pressure increment was established. A material model based on this relationship is developed in this thesis for saturated granular soil under cyclic simple shear conditions. The model includes a hysteretic stress-strain relationship, volume compaction, pore water pressure rise and dissipation. Using this proposed comprehensive material model, a global mechanical model is constructed to simulate the liquefaction (including consolidation) behavior of a thick horizontal deposit when subjected to horizontal base motion. In this way the coupled problems of dynamic response, pore water pressure rise and consolidation of the deposit under seismic loading can be analysed. The numerical techniques used to solve such problems are discussed in detail. The response of a typical saturated sand deposit under earthquake loading is determined using the proposed model and the results show that the model can predict the various phenomena that saturated sand deposits exhibit during earthquakes. The global model also makes clear the influence of permeability on the liquefaction potential of the soil deposit.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".