ON THE IMPORTANCE OF CONSIDERING MULTIPLE SEASTATE REALIZATIONS WHEN ESTIMATING DESIGN LOADS IN MULTI-DIRECTIONAL SHALLOW-WATER WAVES
Bibliographic record
Abstract
The objectives of this work are to close some of the knowledge gaps facing designers tasked with designing new offshore structures or upgrading older structures located in shallow waters and exposed to energetic multi-directional waves generated by passing hurricanes or cyclones. This will be accomplished by first investigating and characterizing the natural variability of the maximum wave heights and crest elevations found in multiple 2-hour long realizations of several short-crested shallow-water near-breaking seastates. Following this, the variability and repeatability of peak pressures and peak loads exerted on a 1/35 scale model of a gravity-based offshore structure are explored. The analysis focuses on establishing extreme value distributions for each realization, quantifying their variability, and exploring how the variability is diminished when results from multiple seastate realizations and repeated tests are combined. The importance of considering multiple realizations of a design wave condition when estimating peak values for use in design is investigated and highlighted.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/16bCsMd0OMc
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".