Effect of load shape on relationship between dissipated energy and residual excess pore pressure generation in cyclic triaxial tests
Bibliographic record
Abstract
The energy dissipated in soil during cyclic loading can be used to predict the change in the pore-water pressure developed in the soil. To examine whether the energy required to cause liquefaction is dependent on or independent of the load shape applied, a series of 28 cyclic triaxial tests were performed using five different load shapes having a range of cyclic stress ratios. The five load shapes were applied to identically prepared specimens of clean sand and the dissipated energy – pore pressure generation characteristics examined. It was found that that the dissipated energy to cause initial liquefaction was normally distributed and independent of the load shape, although it is seemingly somewhat dependent on duration of loading. A corollary to this finding is that laboratory data from specimens tested using sinusoidal loadings can be used to calibrate the Green, Mitchell, and Polito (GMP) energy-based pore pressure generation model for use in predicting in situ pore pressures in soils subjected to nonsinusoidal loadings (e.g., earthquake loadings). Given the relative simplicity of the GMP model, these findings make the model an attractive alternative to implement in effective stress dynamic response codes.
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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 | 0.006 |
| 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 | 0.001 |
| 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".