Complications in Addressing Liquefaction Vulnerability in Stratified Soils from Building to Cluster to Community
Bibliographic record
Abstract
The existing engineering methodologies for liquefaction mitigation rely on free-field triggering in uniformly layered granular soil deposits. These methods routinely ignore cross-layer interactions in stratified deposits, consequences of softening and various mechanisms of mitigation on building performance, or interactions between and among structures in close proximity of each other. In this paper, through an experimental-numerical study, we show that these methods are unreliable, jeopardizing our ability to assess and mitigate liquefaction vulnerability from building to cluster, and to community scales. Fully-coupled, 3D, dynamic finite element analyses, validated with centrifuge experiments, show that combining ground reinforcement with drainage and densification (e.g., through installation of dense granular columns) can improve foundation’s settlement, but not necessarily to acceptable levels. To achieve desired levels of reduction in settlement, it is critical to minimize the likelihood of clogging in such drains, particularly in the presence of silt interlayers. These methods, however, may increase foundation’s tilt potential, which must be evaluated on a case-by-case basis. Unsatisfactory tilt is often uneconomical to repair, which may lead to the decision to demolish or relocate. And this engineering demand parameter (EDP) becomes particularly difficult to improve in urban settings and in stratified and non-uniform deposits. The combined influence if seismic coupling and stratigraphic variability on mitigation efficacy is shown to be significant in terms of foundation tilt, spectral accelerations, and flexural drifts experienced within the superstructure of both mitigated and unmitigated neighbors. These effects are notable for spacing-to-foundation width-ratios (S/W) as large as 1.0, which are common in cities. Additional measures and technologies may be needed to reduce tilt to acceptable levels in closely-spaced cluster configurations and realistically stratified deposits, while simultaneously strengthening both the ground and structures at an area-level and in a cost-effective and sustainable manner.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".