Characterization method of the Joule heating efficiency of electric textiles and influence of boundary conditions
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 Joule heating textiles are available on the market for a variety of applications. However, their market growth is limited by challenges in terms of quality, for instance with the need to provide a reliable account of the heating to be expected, prevent the occurrence of overheating leading to burns and fires, and ensure the long-term performance when exposed to use conditions such as abrasion and laundering. Standard test methods are a key component to solve these issues of efficiency, safety, and durability. Yet, they mostly remain to be established. In this research, a test method was developed for the characterization of the Joule heating efficiency of electric textiles. It involves measuring the temperature of a heating textile using a thermocouple affixed to its surface while it is powered for an hour. The value of the surface temperature that would ultimately be reached by the heating textile after an infinite heating time and the time for the temperature to enter a slow increase regime are determined by fitting an equation to the temperature-time data. These two parameters provide a quantitative mean of comparison between different heating textiles/conditions. This test method was used to analyze the effect of different experimental conditions on the heating efficiency of four heaters corresponding to different technologies of Joule heating textiles and make recommendations in terms of conditions for a standardized test protocol. These results give some insights towards the development of a robust and universal test method for the quantitative assessment of the Joule heating efficiency of electrical textiles that will ultimately be proposed for standardization to help support the growth of the e-textile industry.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 it