Seismic response of liquefiable backfill supported by sheet-pile with different wall embedment ratios
Bibliographic record
Abstract
Analysis of the seismic design of retaining structures is complex due to the intricate interplay between the response of backfill soil and supporting wall. When dealing with liquefiable soils, numerical modeling is often employed to gain insight into the mechanisms behind the resulting deformation of retaining walls during earthquakes. This paper focuses on detailed numerical modeling of two well-documented centrifuge tests of such systems from the last two rounds of LEAP, with different embedment ratios and shaking intensities, and their impacts on the system response of the sheet-pile wall supporting a liquefiable submerged deposit. First, a soil constitutive model is calibrated using data from cyclic direct simple shear tests. The two centrifuge models with different wall embedment ratios and shaking intensities are then simulated and used for validation and assessment purposes. The numerical model shows a successful performance in capturing the system response for both models. Assessing details of the stress-strain response in the numerical model reveals two dominant cyclic deformation mechanisms in the backfill soil: cyclic mobility and the accumulation of residual deformation. The success of the adopted numerical approach in capturing the experimental results is attributed to the constitutive model's ability to simulate both of these cyclic deformation mechanisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".