Technological advancements for anti-icing and de-icing offshore wind turbine blades
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Due to the abundance of wind resources in marine environments, offshore wind turbines (OWTs) have gained significant attention in recent years. However, their blades are prone to ice accretion when operating in cold climates. Ice accretion on OWT blades induces surface roughness thereby reducing the aerodynamic performance of the turbine. Although various ice mitigation techniques have been explored, tested, and applied to onshore wind turbines, their feasibility for offshore application remains uncertain. Therefore, this review conducts a comprehensive feasibility study, examining each ice mitigation technique, its fundamental principles, advantages, disadvantages, and the potential for successful integration on OWT blades. The study also highlights the challenges of implementing these techniques in harsh offshore environments, providing critical insights for future research in this field. • This article reviews techniques for preventing ice accretion on wind turbine blades, focusing on OWT. • It explores various passive and active anti-icing methods, analysing their principles, advantages, challenges, and impacts. • The review concludes that a hybrid approach of SHC and thermal heating offers promising potential for energy efficiency.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it