Numerical simulations of seismic and post-seismic behavior of tailings
Bibliographic record
Abstract
Several tailings impoundments have failed as a result of earthquakes in the last few decades. A majority of these failures were due to direct seismic loading, tailings liquefaction during shaking, or the post-seismic behavior of the tailings as it relates to the dissipation of excess pore-water pressures that were generated during shaking. Previous work has indicated that the UBCSAND model developed by Byrne et al. in 1995 is capable of simulating the cyclic simple shear testing response of low-plasticity tailings over a range of consolidation stresses and cyclic shear ratios. However, the ability of the model to simulate the dynamic and subsequent behavior of such tailings for other conditions, such those induced by shaking table tests, has not yet been evaluated. In this regard, previous work has shown that the main components of the UBCSAND model cannot realistically simulate some specific responses, including the post-seismic volumetric strains related to excess pore-water pressure dissipation. This paper presents numerical modeling results of the dynamic behavior of tailings from hard rock mines. It introduces a method for simulating their post-seismic behavior by including an updating scheme for the elastic moduli into the UBCSAND model. The results of cyclic simple shear testing, seismic table testing, and complementary experimental relationships were used to calibrate and validate the model with its new component. The simulated response of tailings during cyclic simple shear testing and for a complete seismic table test shows that the proposed approach simulates the experimental observations well. Level-ground, seismically induced liquefaction and post-seismic behavior of a 15 m thick tailings deposit are also simulated, leading to post-liquefaction settlements that are in agreement with empirical relationships.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".