Feasibility Study for Small Scaling Flywheel-Energy-Storage Systems in Energy Harvesting Systems
Bibliographic record
Abstract
Abstract Two concepts of scaled micro-flywheel-energy-storage systems (FESSs): a flat disk-shaped and a thin ring-shaped (outer diameter equal to height) flywheel rotors were examined in this study, focusing on material selection, energy content, losses due to air friction and motor loss. For the disk-shape micro-FESS, isotropic materials like titanium, aluminum, steel and wolfram are shown to be suitable as a flywheel rotor. Wound fiber reinforced composite plastics (T1000-, T300-carbon fibers and carbon nanotubes “CNTs”) were investigated for the flywheel in a ring shape. It was shown that isotropic materials reach the highest energy densities in the shape of a Laval disk with a rim. A micro-FESS with wolfram flywheel would reach the highest half-time-periods due to its high density, and thus, it is the favored material to design a flat disk-shaped micro-FESS with low standby-losses. Fiber reinforced plastic flywheels in ring shape reach the highest energy densities, from 150 W h/kg (T300) to 2,600 W h/kg (CNT), but display higher standby-losses as well. A scaling of the rotors was done within this study and showed that air friction is influenced by the shape of the examined flywheel rotors and the material. A linear correlation of down scaling and air friction losses was shown. As a motor/generator type, an ironless air coil Halbach array motor was suggested. Motor losses due to eddy currents in the stator coil were estimated. Losses correlated in square with downscaling. FESSs with wolfram and CNT showed the lowest standby-losses due to eddy currents.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".