Numerical Simulation of Landslide Impulsive Waves by WC-MPS Method
Bibliographic record
Abstract
Numerical simulation has been widely used for solving engineering-related problems in the past few decades. Because of the flexibility, efficiency, and compatibility of numerical simulation, it has been involved in various engineering and science areas. This approach is capable of interpreting the natural phenomena, and also offering an alternative way of theoretical studies and experiments. In this study, the weakly compressible moving particle semi-implicit (WC-MPS) method is applied to simulate the impulse waves generated by landslide. During this study, the complete theory of the WC-MPS model was applied/adopted. The model was modified to simulate the impulse wave for the different landslide cases. This study includes the simulations for the submerged and un-submerged landslide cases, the introduction of deformable and solid sliding blocks, and also the first-hand comparison between WC-MPS simulation and experiments. After comparing WC-MPS simulation with experimental results for different cases, the applicability of WC-MPS method in simulating the impulse wave generated from landslide is confirmed at the end of this study.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".