Approaches to the stability analysis of slopes subjected to seismic loading: A review
Bibliographic record
Abstract
• Offering a comprehensive review of existing seismic slope stability analysis methods and providing a valuable resource for geotechnical engineers to identify the most effective Seismic Slope Stability Analysis methods for different scenarios. • Comparing various analytical and numerical methods and highlighting their respective advantages and limitations. • Exploring diverse load application techniques in seismic stability analysis and shedding light on the critical factors influencing the accuracy and reliability of slope stability assessments during earthquakes. • Identifying the key parameters and conditions affecting the performance of different seismic slope stability analysis methods and offering insights into optimizing these approaches for improved safety and accuracy. The recurrence of slope failures during past catastrophic earthquakes has led to substantial loss of life and structural damage. As a result, assessing earthquake-induced landslides remains a critical focus in geohazard research. While numerous methods have been developed to evaluate the seismic stability of slopes, they vary in assumptions and accuracy. However, most approaches follow one of two fundamental philosophies: calculating a factor of safety (FS) against sliding failure or estimating the permanent displacement upon failure. This paper provides a comprehensive review of various analytical and numerical approaches used for seismic slope stability analysis, serving as a guideline for selecting the most suitable method for evaluating earthquake-triggered landslides. The strengths and limitations of each approach are highlighted to aid in informed decision-making. The primary methods discussed include the pseudo-static approach, the pseudo-dynamic approach, the permanent displacement technique, and stress-deformation analysis. Additionally, advanced approaches with potential applications in large deformation seismic analysis of slopes are examined. Findings indicate that while stress-deformation analysis offers several advantages over pseudo-static, pseudo-dynamic and permanent displacement methods, these benefits come at the cost of increased complexity, requiring more time and effort for problem formulation, material characterization, result interpretation, and significantly higher computational resources. Ultimately, the selection of an appropriate method should be based on the required level of accuracy, project-specific needs, available data, and the complexity necessary to capture the critical aspects of the problem.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".