Field Investigations and Experimental Modelling of the Tsunami-induced Extreme Hydrodynamic Forces on Structures
Bibliographic record
Abstract
A comprehensive research program on tsunami-induced forces on infrastructure located in coastal areas was initiated at the Department of Civil Engineering of the University of Ottawa, Canada, in collaboration with the Canadian Hydraulics Centre, National Research Council of Canada. The paper is presenting some of the results of this interdisciplinary project undertaken by coastal and structural engineers. This research project spanned over a period of six years and included posttsunami field reconnaissance missions as well as physical and numerical modelling of the tsunamiinduced hydrodynamic forces on buildings and their component structural elements. The authors have conducted several field investigation following the 2004 Indian Ocean Tsunami (Thailand, Indonesia, Sri Lanka, and Tanzania) and, more recently, following the February 2010 Chilean Tsunami. One of the goals of this research project is to contribute to the understanding of the complex hydrodynamic mechanisms of impact and extreme loading on nearshore buildings located in tsunami-prone areas. At the same time, this project attempts to improve the quantitative estimation of these hydrodynamic loads and to further propose new formulations for the design of inland structures located in areas which affected by potential tsunami wave attack. The paper presents some brief information on the post-tsunami reconnaissance missions, and in more detail, partial results of the experimental program.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".