Study on wake-induced fatigue on wind turbine blade based on elastic actuator line model and two-dimensional finite element model
Bibliographic record
Abstract
Atmospheric and wake turbulence have a great and immediate impact on the fatigue life of wind turbine blades. Generally speaking, wake-induced fatigue accounts for 5%–15% increase of fatigue load on the wind turbine rotor, which definitely threats the safety and economy of the whole wind farm. However, this effect is difficult to simulate which involves multi-wake interaction and fluid structure interaction. To better simulate the wake-induced fatigue on wind turbine blades, a novel elastic actuator line model is employed in this study. The elastic actuator line is a two-way coupling model, consisting of traditional actuator line model and one-dimensional implicit or explicit finite difference method beam structural model, among which the beam model takes gravitational force, aerodynamic force and centrifugal force into consideration. Large eddy simulation method in the NREL SOWFA code is employed to model the turbulence effect, including wake-induced turbulence and atmospheric turbulence. For the fatigue analysis part, the fatigue life of an NREL 5MW turbine blade subjected to upstream wind turbine wake effects is studied using the elastic actuator line model and laminate data available from Sandia Laboratory in the United States. First, the strain and stress on different composite materials, such as uniaxial carbon fibre and biaxial composite material, are recovered by using the sectional force and moment obtained with the one-dimensional beam model and two-dimensional finite element method model, namely BECAS. Second, the stress-life method, rain-flow counting method, shifted Goodman diagram (constant life diagram) and Miners rule are employed to estimate the fatigue life for different composite materials. Noticeably, elastic actuator line largely reduces the computational efforts compared with a high-resolution computational fluid dynamics model, in which each wind turbine blade is fully resolved. Both the characteristics of different composite materials and airfoil geometries will be considered during fatigue analysis. As a result, the above procedure makes the fatigue life estimation more reliable and feasible. In the case studies, the moment time series predicted by elastic actuator line and FAST are compared. The fatigue damage of NREL 5MW wind turbine under turbulent neutral atmospheric boundary layer is calculated, and the fatigue critical section is determined to be at 10.25 m section from root. Finally, in the study of two in-line turbines, the fatigue damage increase by wake flow is 16%, which is close to the results from previous studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".