DC-Arc Models and Incident-Energy Calculations
Why this work is in the frame
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Bibliographic record
Abstract
There are many industrial applications of large-scale dc power systems, but only a limited amount of scientific literature addresses the modeling of dc arcs. Since the early dc-arc research focused on the arc as an illuminant, most of the early data was obtained from low-current dc systems. More recent publications provide a better understanding of the high-current dc arc. The dc-arc models reviewed in this paper cover a wide range of arcing situations and test conditions. Even with the test variations, a comparison of dc-arc resistance equations shows a fair degree of consistency in the formulations. A method for estimating incident energy for a dc arcing fault is developed based on a nonlinear arc resistance. Additional dc-arc testing is needed so that more accurate incident-energy models can be developed for dc arcs.
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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 | 0.001 |
| 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