Wave Load Prediction on a Stationary Bergy Bit Near a Fixed Offshore Platform
Bibliographic record
Abstract
Offshore oil and gas operations conducted in harsh environments such offshore Newfoundland may pose additional risks due to collision of smaller ice pieces and bergy bits with the offshore structures, including their topsides in the case of gravity based structures particularly in extreme waves. In this paper, CFD (Computational Fluid Dynamics) prediction for wave loads acting on a bergy bit around a fixed offshore platform is presented. Often the vertical column of a gravity based structure is designed against ice collisions, if operating in such an environment. In practices, topsides are usually protected by being placed sufficiently high from the still water level, away from the reach of the bergy bits. This vertical clearance between the still water level and the topside deck is known an air gap. Hence, the amount of the air gap planned for such an offshore structure is an important factor for the safety of the topsides at a given location. In this study a CFD method is applied to estimate the dynamic response of the bergy bit and provide a reliable air gap to reduce the potential risk of the bergy bit collision. In advance of more complex collision simulations using a free-floating ice for the airgap design, CFD analysis of wave load prediction on a stationary bergy bit is carried out and reported in this paper. In the experiments and CFD simulations, the location of the bergy bit is changed to quantify the change of wave load due to the hydrodynamic interaction between the bergy bit and the platform. Finally, the results of the CFD simulations are compared with the relevant experiment results to confirm the simulation performance prior to the free floating bergy bit simulations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".