Material point method (MPM) hydro-mechanical modelling of flows impacting rigid walls
Bibliographic record
Abstract
The study on impact mechanisms of flow-like landslides against structures is still an open issue in the scientific literature. Many researchers have so far employed either experiments or numerical methods, but the evaluation of the impact forces on mitigation obstacles remains difficult especially if the solid–fluid interaction within the flow is considered. This study shows how advanced numerical tools, such as material point method, may be used in simulating those complex processes. The simulations are carried out for two well-documented laboratory tests: a dry granular flow impacting a rigid wall under different geometries and testing conditions in a small-scaled flume and a saturated flow with complex propagation pattern in a centrifuge apparatus. The numerical modelling is validated against the observations and then used to explore the response of different flows impacting rigid structures in other conditions than in the experiments. The soil–fluid interaction influences the type of impact mechanism, the kinematics of the flow, and the space–time trend of the impact pressure against the structure.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.001 |
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".