Bibliographic record
Abstract
This paper expands on the relationship between fault interrupting speed versus incident energy. It will provide some details about the world's fastest low voltage (LV) circuit breaking technology. With ultra-fast and consistent clearing times, devices using this technology provide the fastest method of removing fault currents. This sequentially reduces fault incident energies to nearly non-existent levels. Adding this switching technology could be the next step in enhancing your safety program. This new and very rapidly growing technology is the LV Solid-State Circuit Breaker (SSCB). Using silicon carbide (SiC) semiconductor modules, and unique current sensing methodologies, furnishes the SSCB with the ability to provide extremely rapid, consistent, and arc-less switching. Since the interruption of the current is performed without any electro-mechanical contacts, these devices can provide an almost unlimited number of switching operations. While at the same time, release virtually no arc flash incident energy whilst also limiting the let-through current to the lowest level in industry. In this work, we will provide an overview of this new technology and how Petroleum and Chemical industry users can take advantage of eliminating almost all release of arc flash incident energy associated with traditional LV molded case circuit breakers (MCCB). And, at the same time, significantly reduce the electromechanical stress on the connected load while virtually eliminating the need for breaker maintenance providing a protection device with a much higher mean time between failures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".