Numerical simulation of earthquake-induced pore pressure response of saturated sand layer in a partial drainage environment
Bibliographic record
Abstract
The earthquake-induced pore pressure response of a 5-m clean Ottawa F-65 sand layer of 45% relative density, under an effective overburden of 1 atm and subjected to earthquake base excitation, is numerically simulated. The layer sits on an impervious boundary and is free to drain at the top to simulate a possible partial drainage condition in the field. Numerical software FLAC and constitutive model PM4Sand are used for the simulation. The model is calibrated using the results of an available high-quality centrifuge experiment conducted in the Geotechnical Centrifuge Facility at Rensselaer Polytechnic Institute. Extensive instrumentation was utilized in the experiment to measure the dynamic soil response, including time histories of acceleration, pore water pressure and displacement, as well as bender elements measurements of shear wave velocity. Furthermore, System Identification is used to back-figure time histories of shear stress and shear strain. The instrumentation at different elevations in the experiment provided a comprehensive coverage of the soil response, which supported a system-level model calibration. A brief parametric study of the model’s input parameters preceded the model calibration in order to investigate how they affect the system-level behavior and to establish a proper calibration procedure. The predictions of the calibrated model are in excellent agreement with the records from the centrifuge, providing a strong basis for using the calibrated model to extend the results of the centrifuge experiment to other earthquake input motions, sand layer thicknesses and drainage boundary conditions. The calibrated numerical simulation was repeated after changing the layer thickness from 5 m to 10 m. The results of the new simulation are discussed to illustrate the possibilities of the new calibrated numerical tool.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".