PHYSICAL AND NUMERICAL MODELLING OF THE FLOW STRUCTURE BEHIND STRUCTURE IN TSUNAMI-LIKE FLOW
Bibliographic record
Abstract
Coastal structures are expected to play a role as evacuation buildings. Numerous studies have been examined tsunami-induced wave force acting on an inland building (Shigihara et al., 2009; Arimitsu et al., 2014). In addition, coastal structures have the potential to obstruct inundating tsunami waves, protecting structure further from the coastline. Hydraulic experiments and numerical calculations on shielding effect are being carried out. Alternatively, the vortices from these structures can result in significant scour downstream, influencing downstream structure stability. In the 2011 Tohoku Region Pacific Offshore Earthquake, many cases were reported that the structure was scrubbed and the structure fallen down. Skakiyama et al. (2007) and Sakakiyma et al. (2008) pointed out that the standing vortex generated around the structure winds sand and causes scouring. Therefore, understanding the vortices generated around the structure is also important in predicting the scouring phenomenon. As such, the flow properties around coastal structures must be considered and acknowledged within the design process. However, there are a few studies focusing on the flow fields behind structure.Arnason et al. (2009) measured velocity fields of dam-break flow around/in the wake of a vertical column. Wei et al. (2015) reproduced the experiment performed using SPH. However, in the experiment, vortexes are not considered and the influence of the existence of structures on the surroundings has not been sufficiently considered. Therefore, in this study, the flow fields of a tsunami-like wave around structures were examined through hydraulic experiments. This experiment was performed to clarify the local vortex structure behind structures by measuring the plane flow velocity field. Also, the effect of obstructing protecting the land side structure is assessed by measuring the wave force behind structures. Furthermore, a three-dimensional model (OpenFOAM) was used to further analyze the flow, focusing on water-level and wave forces behind 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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".