Three-dimensional slope stability study using a Coupled Eulerian-Lagrangian method
Bibliographic record
Abstract
<p>  In slope stability analysis, two-dimensional (2D) analysis techniques are usually applied due to its simplicity and extensive applicability. Given that slope failures are three-dimensional (3D) in nature, especially in the slope with complex geometry, a 3D slope stability analysis could lead to more reasonable results [1]. In slope stability analyses, limit equilibrium method (LEM) and finite element method (FEM) are widely used. Note that LEM only satisfies equations of statics and does not consider strain and displacement compatibility; FEM may encounter significant mesh distortion during large deformations where convergence difficulty and the analysis may be terminated before the slope reaches failure [2]. In the study, a Coupled Eulerian-Lagrangian (CEL) method, which allows materials to flow through fixed meshes regardless of distortions, was utilized to investigate 3D slope stability [3]. Validation of the numerical modeling was first presented using a typically assumed 3D slope. After the validation, various types of slopes (i.e. turning corners, convex- and concave-shaped surfaces) with various boundary conditions (unrestrained, semi-restrained, and fully restrained) are carefully conducted to examine the 3D slope stability. It is anticipated the 3D analyses can shed some light on the slope stability analysis with extreme or complex geometry cases and provide more reasonable results.</p><p> </p><p>REFERENCE</p><ol><li>T.-K. Nian, R.-Q. Huang, S.-S. Wan, and G.-Q. Chen (2012): Three-dimensional strength-reduction finite element analysis of slopes: geometric effects. Canadian Geotechnical Journal, 49: 574–588.</li> <li>C. Hung, C.-H. Liu, G.-W. Lin and Ben Leshchinsky (2019): The Aso-Bridge coseismic landslide: a numerical investigation of failure and runout behavior using finite and discrete element methods. Bulletin of Engineering Geology and the Environment. doi: 10.1007/s10064-018-1309-3.</li> <li>C. Han. Lin, C. Hung and T.-Y. Hsu (2020): Investigations of granular material behaviors using coupled Eulerian-Lagrangian technique: From granular collapse to fluid-structure interaction. Computers and Geotechnics (under review).</li> </ol><p> </p><p> </p>
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".