Comparison between constant-volume and fully undrained cyclic simple shear tests using the strain-based energy concept
Bibliographic record
Abstract
The cyclic direct simple shear (C DSS ) test has been widely used for dynamic analysis, including soil liquefaction. C DSS enables the replication of shear wave propagation and considers more representative stress conditions during earthquakes. Several studies have investigated the drawbacks of C DSS, including the prominent artificial pressure jump ( R u ∗ jump ) produced in the first few cycles during constant-volume tests, as demonstrated in the pioneer works of Prevost and Høeg (1976) [37]. However, the effect of this pressure jump on the overall C DSS results, including the number of cycles to produce liquefaction or cyclic mobility, has not yet been investigated experimentally. Therefore, this study investigated this aspect using a series of strain- and stress-controlled fully undrained triaxial simple shear ( T x SS ) and constant-volume C DSS tests. Strain-controlled test results were used to establish relationships between dissipated energy and R u to examine the difference between the fully undrained and constant-volume tests conducted on the same basis. The results show that the artificial R u ∗ leads to the overestimation of the R u values and underestimation of the cyclic resistance. However, consistency between the C DSS and T x SS results was achieved after correcting the R u ∗ jump error. The agreement between the experimental and numerical results confirms the efficiency of the stain-based energy concept to improve the cyclic C DSS test results.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.002 | 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".