Do Rock Design Formulas Based on Wave Flume Experiments Reliably Model Their Performance at Sea?
Bibliographic record
Abstract
The mean sea level rising predicted for this century and the following centuries will make necessary to protect most of the human properties located on the coast. One of the alternatives is the construction of slope breakwaters along hundreds of kilometers of coastline. For coastal engineering this task is a social/environmental and economic/financial challenge, in particular the optimization of the total costs of the structure during its useful life. It is common to design these structures with the Van der Meer stability formula, assuming that the uncertainty of the project is due to maritime agents. Today, this approach is no longer valid and must be reconsidered to adapt to the social and environmental demands. The main source of uncertainty of the Van der Meer formula is epistemic, associated with its ability to predict the progression of failure modes of the structure. This study analyses the actual formula of design coastal structures and discusses the limitations for predicting damage progression, which directly affects designing strategies and total lifetime conservation and repair costs of the structure. It is shown that these limitations derive from: (1) design and experimental technique of the wave flume to propose the formula; (2) non-dimensional variables and parameters included in the formula; and (3) the method of application. It seems desirable and urgent to review and update the state of knowledge and tools for slope breakwater design to meet the demand for protection of human properties on the coast.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".