Numerical Modelling of Extreme Hydrodynamic Loading on Coastal Structures
Bibliographic record
Abstract
Natural disasters usually occur without any warning. They can leave trail of destruction and cause much tragedy. We are at a time when we witness fast technological advances; hence, we need to apply the force of scientific advancements to decrease economic losses and the number of human deaths. Tsunami is one of the extreme environmental events that leaves nothing but a path of death and destruction, and as a result, it is essential to understand this phenomenon and identify the mitigation strategies. Several mitigation strategies have been proposed so far; however, more investigations are still required to achieve an acceptable solution. Researchers around the world are studying different aspects of this phenomenon. One of the proposed solutions that has received much attention is designing tsunami-resistant structures which can withstand the force of a tsunami bore. Various studies have been done so far to understand the base shear force of tsunami bore on structures. The focus of this thesis is to improve and better understand the characteristics of the tsunami base shear forces on structures. Hence, in this thesis, two numerical studies were proposed and performed with the main goal of estimating the total tsunami forces on structure under two different conditions. Those include structures with various cross sections, as well as positioning a mitigation wall at an appropriate location relative to the structure. The first study focused on developing a numerical model to study the relationship between tsunami forces and the geometry of the structure. The main goal of this study was to define a numerical model capable of simulating this case precisely. To ensure the accuracy of the model, a comparison was carried out between the results of the numerical model and experimental test performed at the NRC-CHC (National Research Council- Canadian Hydraulics Center) laboratory in Ottawa, Canada and Université Catholique de Louvain (UCL), Belgium, which revealed a very good agreement between the results of the experimental test and numerical model. Further, the validated model was applied to investigate the tsunami force on structures with various cross sections. The second study focus was on developing a numerical model for understanding the role of mitigation wall (a novel idea proposed as a mitigation strategy by the second author of technical paper 2) on reducing the exerted force of tsunami on structures. After developing various models and applying several turbulence models, a valuable result was obtained which demonstrated that a Large Eddy Simulation (LES) model seems to be an excellent approach for predicting the tsunami forces on the structure with a mitigation wall in the direction of the flow. The results of this study will be used to better estimate the tsunami forces exerted on coastal structures which will light the path to the main goal of designing tsunami resistant-structures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".