Arc-Flash Risk in Low-Voltage Single-Phase Power Distribution: Improving Confidence in Arc-Flash and Electric Shock Equipment Labeling
Bibliographic record
Abstract
National Fire Protection Association 70E and Canadian Standards Association Z462 require a qualified person to perform an electrical hazard assessment—including arc flash risk—for activities involving exposed, energized conductors or when interaction based on a work task could create an abnormal arcing fault. IEEE 1584-2018 “Guide for Performing Arc-Flash Hazard Calculations” documents the commonly accepted method for calculating arc-flash incident energy at an assumed working distance and the arc-flash boundary distance, for 208-V ac to 15k-V ac three-phase electrical equipment. While IEEE 1584 covers three-phase systems in detail, neither of the 2002 or 2018 editions provide modeling methods for single-phase systems. Single-phase 230-V and split phase 120/240-V ac power are the standard for residential and light commercial distribution around the world, and single-phase electrical equipment is common in industry. This article describes single-phase arc-flash experimental work conducted in 2020 as part of doctoral study and underpinning a dissertation. The principal investigator’s (PI’s) goal was to improve confidence in arc-flash and electric shock equipment labeling practices in support of his role as an industrial plant chief electrical engineer. The experimental hypothesis was: There is an available system energy threshold below which arc-flash incident energy would be low (less than 1.2 cal/cm2).
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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 | 0.010 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".