Design Space Exploration of Centimeter-Scale Wind Turbines using a Physics-Modified Optimization Formulation
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
Abstract This paper explores the design space of centimeter-scale micro wind turbines to power wireless sensors through an experimentally validated modeling and simulation environment. A stochastic optimizer is used to obtain a functional relationship between the minimum wind velocity required to find a feasible design and multiple constraints relevant to turbine designers, such as the maximum turbine radius, electrical power required, minimum voltage required and available generators. This relationship is created from an optimization formulation that uses knowledge from the underlying physics and previous optimizations. It is shown that the design space of micro wind turbines is significantly different than large wind turbines due to the low Reynolds number regime. Also, a strong coupling exists between the choice of generator and optimal wind turbine geometry to minimize the wind required to meet the requirements. Smaller generators are more appropriate for micro wind turbines only if a constraint is applied on the maximum radius of the turbine and if no minimum voltage is required for a fixed power output.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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