Towards a Framework for Aero-elastic Multidisciplinary Design Optimization of Horizontal Axis Wind Turbines
Why this work is in the frame
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Bibliographic record
Abstract
Multi-disciplinary Design Optimization (MDO) has been successfully applied in the aerospace industry, so given the similarities to wind turbine design, the application of MDO techniques is a potential opportunity to improve wind turbine design. MDO attempts to solve for optimal design parameters by considering the performance of multiple disciplines simultaneously. This approach differs from sequential optimization in which each discipline is optimized separately. Evaluating the design with a comprehensive approach leads to better balanced designs. This article presents a Multi-Disciplinary Feasible (MDF) framework that incorporates an aerodynamics code based on vortex methods with a nonlinear beam formulation for the blade aerodynamics and structural dynamics, in order to eventually study non-straight blades with arbitrary composite layups. In the current work, the framework is exercised to optimize a conventional design for a 100 m blade. It was found that obtaining accurate coupled gradients for a fully-relaxed wake simulation using explicit aerodynamic solution methods is very challenging. A rigid wake approach enabled more reliable convergence, and suggestions are given for future work in applying MDO to this class of wind turbine analysis methods.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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