Numerical modeling of liquefiable slopes using Hypoplasticity with ISA and semifluidized states: Benchmarking against LEAP centrifuge data
Bibliographic record
Abstract
This study analyzes numerical simulations of a water-saturated, liquefiable sandy slope centrifuge test subjected to dynamic base excitation. The benchmark centrifuge experiment was executed within the scope of the LEAP-2017 project by Carey et al., (2020) . Numerical simulations were conducted in PLAXIS, a finite element modeling software, with the soil’s mechanical behavior modeled through a recently developed hypoplastic model for sands, accounting for semifluidized states and fabric change effects, as proposed by Tafili et al., 2024. The constitutive model was carefully calibrated using element tests performed with Ottawa F-65 sand, which was also employed in the centrifuge test. The dataset comprised oedometric compression tests, drained and undrained monotonic triaxial tests, and undrained cyclic triaxial tests, considering different initial densities and effective stresses. A comparison of measured and predicted results revealed reasonable agreement in terms of acceleration time history, spectral response, and the evolution of excess pore water pressure. These findings provide a comprehensive assessment of the predictive capabilities and limitations of the constitutive model in forecasting the behavior of geotechnical structures under earthquake loading.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".