Simulation of Free-Surface Flow Using the Smoothed Particle Hydrodynamics (SPH) Method with Radiation Open Boundary Conditions
Bibliographic record
Abstract
Abstract The smoothed particle hydrodynamics (SPH) technique is a mesh-free numerical method that has great potential to be used in the development of the next generation of numerical ocean models. The implementation of open and solid boundary conditions in the SPH method, however, is not as straightforward as the mesh-based numerical methods. Two types of open boundary conditions are considered in this study: the adaptive open boundary condition (AOBC) and Flather’s open boundary condition (FOBC). These two open boundary conditions are implemented in the SPH-based shallow-water equation (SWE) circulation model for simulating sea surface elevations and depth-mean currents over a limited area with open boundaries. The performance of these two open boundaries is assessed in four numerical test cases. In comparison with the conventional characteristic open boundary condition, both the AOBC and the FOBC allow perturbations to propagate out more effectively and are easy to implement with the specification of external flow conditions at the model open boundaries. The model results also demonstrate that the AOBC requires an accurate estimation of the phase speed of perturbations and could lead to a small drift in the mean water level. By comparison, the FOBC is computationally more efficient without any model drift. The SPH-based SWE circulation model is also used in simulating the laboratory observations of the 1993 Okushiri Tsunami. The numerical results in this case demonstrate the feasibility and capability of the SPH-based SWE model for simulating free-surface flows in regions with complicated bathymetry and irregular coastline.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".