One- and two-dimensional seismic analysis of solid-waste landfills
Bibliographic record
Abstract
The results from one-dimensional (1D) and two-dimensional (2D) dynamic response analyses are compared to determine the reliability of the common practice of using 1D analysis to evaluate the seismic response of solid-waste landfills. Results indicate that 1D analysis generally provides a reasonably conservative estimate of the seismic loading and earthquake-induced permanent displacement for deep sliding surfaces, such as along the base liner. However, caution is warranted for shallower sliding surfaces, where 2D topographic amplification often results in larger values of seismic loading and permanent displacement than that predicted by 1D analysis. The 1D2D analysis comparison is not just a function of geometry, but is also dependent on the different numerical formulations typically employed in each procedure (e.g., 1D wave propagation versus 2D finite element). Comparisons of accelerations along the landfill surface indicate that 1D analysis consistently under predicts the maximum horizontal acceleration (MHA) along the slope near the crest of the landfill. However, the seismic loading is shown to vary systematically with normalized cover slope length, with the maximum equivalent acceleration for the full cover slope being about 40% of the peak acceleration at the crest. Based on the results of this study, a simplified procedure is proposed for scaling 1D results to account for 2D topographic amplification and cover slope averaging when evaluating the seismic performance of landfill cover systems.Key words: solid-waste landfill, dynamic response, seismic loading, finite element analysis, Newmark sliding block analysis, damping.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".