MPS-Based Mesh-Free Particle Method for Modeling Open-Channel Flows
Bibliographic record
Abstract
Dealing with large deformation and fragmentation of geometries and interfaces (e.g., free surfaces), the regular mesh-based Eulerian methods, such as finite-element and finite-difference methods, have difficulties in fluid-flow modeling. Recently, studies have focused on a new generation of numerical methods called mesh-free particle (Lagrangian) methods. In this study, a mesh-free particle method based on the moving-particle semi-implicit (MPS) particle-interaction model has been developed for simulation of open-channel flow. The model is able to simulate viscous fluid flow with large deformation and fragmentation of free surface in practical fields. Moreover, the model is capable of modeling open-channel problems with both inflow and outflow and inconstant numbers of particles. The model has been validated and applied to some common sample problems. The results show the reasonable accuracy of the model. The final model is capable of modeling free-surface deformation and fragmentation as well as accurate calculation of velocities in open channels.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".