Bibliographic record
Abstract
This paper describes the design and the main technical characteristics of a new start system for an aircraft auxiliary power unit (APU). By using the latest improvements in power electronics and microelectronics, this system eliminates the conventional DC starter by driving the generator installed on the APU as a motor to achieve the start. The developed start system eliminates one battery, dedicated for APU starting, the DC starter and its clutch assembly, while providing a faster start, assisting the APU acceleration up to 8,400 rpm (vs. 6,000 rpm provided by the DC starter). This new system extends the APU life by maintaining lower engine temperatures during start. The battery voltage control feature, that maintains this voltage at 18/20 VDC during start and the option of using AC power for start, to save battery power is another advantage over the classical DC. This new start system is installed in over 650 commercial airplanes and the operation in revenue service has proved its high reliability. Presently its MTBF is 600% higher than the time between overhauls (TBO) for the DC starter, while assuring an increased performance and safety in operation.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".