Impact Loads and Protection of Subsea Structures on the Seabed from Floating Iceberg Keels
Bibliographic record
Abstract
Abstract In iceberg prone regions, subsea substructures placed on the seabed are atrisk of impacts from free-floating and scouring iceberg keels. Here themethodology for assessing iceberg loads and two mitigation strategies aredescribed. The iceberg load model was an extension of previous work forestimating iceberg impact loads on offshore surface-piercing structures. Components of the algorithms were modified such that global design loads fromkeel contacts account for the change in contact location (i.e., longer leverarm in the vertical direction resulting in greater rotation effects). Theiceberg eccentricity model and the relationship between contact area andpenetration distance were also modified to account for iceberg keel contactswith a generic low profile structure on the seabed. One concept considered wasa single wellhead structure fitted with a special weak shear link incorporatedinto the design at the expected scour level. The shear link, or failure joint, would act as a mechanical fuse designed to fail in a combination of shear, tension and buckling during keel loading. The failure joint minimizes downholestructural response during iceberg keel loading on the production tree. Thedesigned failure mechanism would allow the well to be re-entered by protectingthe well casing from damage. Another concept considered was a steel truncatedcone structure installed over the well installation and fixed to the seabed byone of several identified foundation concepts. The protection structure absorbsenergy through crushing of the ice keel and encourages the iceberg to deflectaround and over the structure. The steel structure would be designed accordingto ultimate limit states accounting for energy absorption through elastic andplastic deformation of the structure. Design loads would correspond to anAbnormal Level Ice Event (ALIE) with an annual exceedance probability of 10–4. The size of the frame is governed by the size of the wellhead and tree system, Remotely Operated Vehicle (ROV) access requirements, and slope to encourageiceberg keel deflection. Piles may be the best option for securing a protectionstructure to the seabed, especially if a local vessel can be sourced to performthe installation. As an alternative to piles, using a drill rig to install wellcasings may be an option; however, market conditions for drilling rigs maydictate economic feasibility.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".