LEAP-ASIA-2019 Simulations at Tsinghua University
Bibliographic record
Abstract
Abstract This chapter presents the constitutive model calibration and numerical simulations of centrifuge shaking table tests for LEAP-ASIA-2019, at Tsinghua University. A plasticity model that can provide unified description for the behavior sand at different states under both monotonic and cyclic loading, with focus on the large post-liquefaction shear deformation, is calibrated and used in this study. New undrained cyclic torsional shear test results for Ottawa F65 sand provided in the most recent phase of the LEAP project are used in the calibration process. Typical results for acceleration, excess pore pressure, and displacement for one of the tests are presented in detail, showing that the numerical simulation is able to capture the liquefaction related behavior in the tests well. Comparisons between the simulation and test residual displacement results for the five different tests show conflicting results. The simulations for the two RPI tests under different centrifuge acceleration levels with different stress states and input motion frequencies generally show adequate agreement with test results, exhibiting the constitutive model and numerical simulation method’s wide applicability range. However, the simulation results for the KyU tests are significantly different to the 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".