Bibliographic record
Abstract
Cold climate regions have a high potential for wind energy production, but can also be characterized by frequent atmospheric icing events, which can significantly reduce the annual power production of a wind farm. Ice that accretes on turbine blades degrades their aerodynamic performance and reduces their power output. Thus, there is a need for more accurate assessment of the effect of atmospheric icing on wind turbines and for strategies to protect turbine blades from icing.The present work uses CFD analysis to focus on two important engineering issues related to wind turbine blade icing: the wind turbine performance loss due to blade icing, and the design of blade heating systems to prevent ice accretion. All CFD simulations are performed using the FENSAP-ICE simulation system.First, CFD simulations are used to predict the impact atmospheric icing has on wind turbine power production. Fully 3D simulations are performed considering the rotor geometry of the National Renewable Energy Laboratory (NREL) Unsteady Aerodynamics Experiment (UAE) Phase VI rotor. Four representative icing conditions are simulated. The resulting ‘1-hour‘ ice shapes are shown to reduce rotor torque, and therefore resulting power output, by up to 60%. Furthermore, at high wind speeds the NREL turbine blade is regulated by intentional blade stall to prevent very high torque and overproduction. CFD simulations showed that at these wind speeds, ice accretion could increase the wind turbine rotor torque significantly, potentially damaging the turbine due to overproduction and creating possible safety concerns. Next, the FENSAP-ICE system is used to predict the power required and effective coverage region needed for an anti-icing system to prevent ice accretion on the NREL UAE Phase VI rotor. In all cases the power required to keep the rotor ice-free was less than the rated power of the turbine.Lastly, a CFD simulation of a real-world, long-term, 17-hour icing event that took place at a wind farm in the Gaspé Peninsula of Québec was performed. Results of power loss successfully matched that which occurred on site. Moreover, it was determined that an anti-icing system used during a similar icing event could protect against icing in a self-sufficient manner.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".