MULTIPLE IMPACTS OF DEBRIS ON A VERTICAL OBSTACLE
Bibliographic record
Abstract
Past tsunami events have caused extreme damage in coastal regions. Examples are the Indian Ocean Tsunami in 2004 and the Tohuku Tsunami in 2011. These extreme natural disasters brought into light the devastating nature which tsunami-induced inundation might inflict when propagating on-land. As a result of eye-witness reports and extensive media coverage, a wealth of evidence showing multi-phase fluid motion entraining a solid phase consisting of entrained debris, ranging from sediment grains to large vessels became available. In this context, debris impacts have been linked to major infrastructural damage (Yeh et al. 2012). This observation resulted in increased research emphasis on tsunami-driven debris impact. It also initiated the inclusion of first debris impact force equations in existing building codes such as FEMA (P-646 2012) and ASCE (Standard 7-16 Chapter 6). There are however still a lot of uncertainties on factors influencing tsunami-driven debris impact. Besides the random, probabilistic nature of debris entrainment, advection by the entraining flow and the uncertainty related to impact points, no guidance exists as to how multiple impacts of debris can be accounted for. In addition, little focus was directed to impact forces on non-rigid structures which investigated here for the first time.
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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 | 0.000 |
| 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".