Ice Clearing to Support Near-Field Operations
Bibliographic record
Abstract
Abstract Ice management is an important consideration for any offshore petroleum operation conducted in an area that could encounter sea ice. Ice management could be performed for a number of reasons: to reduce global ice loads on the installation, to avoid ice interaction with underwater components such as risers or turrets, or to allow for close proximity operations such as loading / offloading, manning / de-manning, or evacuation in the case of an emergency event. The purpose of this project is to provide baseline information relating to ice clearing operations conducted in pack ice conditions. This information includes outcomes of different ice clearing operations in terms of loads on a GBS structure and ice concentration upstream of the GBS structure. It also includes loads measured on the support vessel that is conducting the ice clearing operations for a subset of the clearing techniques considered. To investigate this problem, model testing experiments were conducted in NRC-OCRE's ice tank located in St. John's NL, Canada. These experiments involved systematic testing involving various pack ice conditions representative of the Grand Banks area and two models: a support vessel and a GBS structure. The environmental conditions included: two ice concentrations, two ice piece sizes, and two ice piece drift speeds. Four ice clearing techniques were tested in each condition. The ice clearing techniques included two fixed position tests; where the support vessel was held in place upstream of the GBS using flexible mooring lines and two free running tests; where the support vessel was remotely controlled and maneuvered upstream of the GBS. Results are provided in terms of loads measured on the GBS model with clearing support, loads measured on the support vessel during the fixed ice clearing operations, ice free zones created upstream of the GBS and aft of the support vessel during ice clearing tests, reductions in GBS loads due to ice clearing operations, reductions in ice concentration upstream of the GBS due to ice clearing operations, and a summary of ice events that led to large pack ice loads. The significant factors that influenced each result were also identified. These results complement existing literature relating to physical ice clearing operations by providing the outcomes of systematic testing in different ice conditions which is available in public domain. These results could be used as benchmark values for design or numerical model validation. In addition, they could provide insight to operators, regulators and academia to support informed decision making regarding the level of ice management support required in different operating environments. All dimensions and test results in this paper are provided at full scale value.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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; both teacher heads agree on what is shown here.
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".