Updating the Iceberg Load Software Using High Resolution Iceberg Profiles
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Bibliographic record
Abstract
Abstract Icebergs can pose a risk to offshore oil and gas structures in arctic and sub-arctic regions of the world. The Iceberg Load Software (ILS) was developed to determine design loads on structures following the spirit of ISO 19906:2010, helping designers better understand the impact forces and moments the structures must be designed to withstand. The ILS is a fully probabilistic model which accounts for the range of iceberg shapes, sizes and strengths, and environmental conditions expected at the platform location. The model is applicable to fixed structures such as a gravity based structure (GBS), as well as floating structures such as a floating production, storage and offloading (FPSO) vessel. Users can incorporate the effectiveness of iceberg detection, physical management, and disconnection (where applicable for floating platforms) in mitigating the risk of impact with an iceberg. The input relationships and distributions used to characterize the iceberg population are based on measured data typically collected in the region. These data include everything from basic measurements such as iceberg length, width or sail height to the more detailed shape information in the form of complete three dimensional iceberg profiles. In 2012, a major field program was carried out (Younan et al. 2016) with the objective of collecting high resolution iceberg profiles to improve the modelling of iceberg shape. Above water shapes were captured using a photogrammetry technique and were merged with below water shapes collected using multibeam sonar. The end product was a database of 28 high resolution iceberg profiles providing considerable information on iceberg shape. The objective of this study was to use the high resolution iceberg profiles to update models characterizing iceberg shape in the ILS. These includes models for area-penetration, contact location and impact eccentricity. In addition, relationships correlating iceberg draft and mass to waterline length were updated using the new profiles. Example simulations were performed for a generic structure using the ILS to demonstrate the influence of the updated models, distributions and relationships on the output design forces and moments.
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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) | 0.001 | 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 it