Evaluation of a Fabric Channel Cooling Apparatus for Twisted Coiled Actuators
Bibliographic record
Abstract
Wearable robotic systems have the potential to help many individuals with rehabilitation and to support activities of daily living. Unfortunately, these systems are not widespread due to their cost, limited portability, and size. Twisted Coiled Actuators (TCA), novel artificial muscles made from nylon thread, are inexpensive, lightweight, and slim. However, the natural cooling time of these thermally activated muscles is too slow to support rehabilitation or voluntary motions. This paper presents and assesses the feasibility of a novel cooling apparatus for the TCA. The cooling method involves a flexible fabric channel and a miniature air pump to cool the TCA with forced convection. The channel is lightweight, flexible, and can easily be sewn onto other materials to allow easy fabrication of wearable devices. ANSYS Fluent simulations were performed to determine the relationship between the input air velocity and the cooling time constant of the system. The results indicate that the miniature air pumps currently available are not powerful enough to cool the TCA at the required frequencies. There was a 13.2% difference between the cooling time constant predicted by the model and the time constant found experimentally for an input of 1 m/s.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".