Modelling and Analysis of Hydrodynamics of a Submerged Structure in Extreme Waves Using a SPH-Based Tool
Bibliographic record
Abstract
Abstract The applications of a Smoothed Particle Hydrodynamics (SPH)-based, a Finite Volume Method (FVM)-based and a Boundary Element Method (BEM)-based tools to investigate the nonlinear interactions between large waves and a submerged horizontal circular structure and to some extent a rectangular cylinder at various submergence depths in deep water conditions are presented. The main aim is to validate the Lagrangian technique based SPH tool to predict the wave-structure interaction forces under large waves. The features of typical force curves in a wave cycle, the magnitude of wave forces, and the influence of relative axis depth of the structure in deep water conditions are investigated, primarily using an open-sourced SPH tool. Simulations were carried out in 2D with one deepwater wave at multiple submergence depths. The water surface elevations are predicted at different near- and far-field locations. The time-averaged mean and the average amplitude of the horizontal and vertical forces acting on the cylindrical model at various submergence depths are plotted and then physically interpreted. The wave forces and surface elevations are compared with the available published experimental studies and CFD (both FVM and BEM) predictions. Good agreement between the SPH predictions and the measurements was obtained for the submerged body’s surface elevation and hydrodynamic forces at all submergence depths. The FVM tends to overestimate the wave forces compared to the SPH predictions and the measurements, particularly for the shallowly submerged structure when extreme wave breaking occurs. The BEM predictions are reasonable for the non-wave breaking cases.
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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) | 0.000 | 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".