A Review of Ice Protection Techniques for Structures in the Arctic and Offshore Harsh Environments
Bibliographic record
Abstract
Abstract Icing can jeopardize local infrastructure, hinder field operation, destroy vessel superstructures, and threaten life and property safety in the Arctic and other cold offshore and marine environments. Research on ice protection (both anti-icing and de-icing) technologies is critical to equipment, structures, and personnel in these environments. This review systematically evaluates a wide range of ice protection techniques divided into three main categories, i.e., active, passive, and hybrid ice protection techniques. Active anti-icing/de-icing technologies include mechanical, thermal, or chemical methods, requiring an additional energy source to prevent ice formation or remove accumulated ice from the target surfaces. Passive anti-icing/de-icing techniques can prevent ice accumulation or reduce ice adhesion without external energy sources; they create and maintain the icephobic properties of the target surfaces. Excessive energy consumption is a major technical limitation of active ice protection technologies. On the other hand, it is challenging for any passive technology to meet the long-term ice protection requirements in the Arctic or different cold offshore/marine environments. A combination of two or more active and passive ice protection methods, i.e., a hybrid approach, seems promising and can be applied in various situations according to the specific requirements of different vessels, offshore structures, and equipment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".