POWER QUALITY ANALYSIS IN A HERCULES AIRCRAFT POWER DISTRIBUTION SYSTEM
Bibliographic record
Abstract
Power system studies can provide useful information on the performance of existing and future systems during both normal and abnormal operating conditions. For example, system studies can reveal harmonics and over-voltage transients, system characteristics which can significantly and adversely affect system performance. The sources of these undesirable characteristics are many and varied, and include transformers, switching transients, nonlinear loads, and devices such as the static power converter. The future use of nonlinear loads is expected to increase since these loads are generally highly efficient. Unfortunately, as the use of these loads increase, waveform distortion is also expected to increase. The resulting waveform distortion will influence overall system performance unless adequate steps are taken to control and maintain power quality. Future advanced aircraft avionics systems will require reliable, redundant, and uninterrupted electrical power to supply flight and mission critical loads. The Canadian Forces CC-130 Hercules aircraft fleet is scheduled for an avionics update that will include complex, sensitive avionics equipment. The power quality required for this update may not be adequate since the existing electrical distribution system was designed to satisfy load requirements of the 1950's. This paper describes the use of Microtran7 software, a transients analysis simulation program, and the development of a laboratory model to predict the CC-130 Hercules aircraft electrical switching transients and steady-state response, including voltage and current harmonic levels on the power distribution system using tabulated equipment load data. The simulation and laboratory results are then compared for validation with field measurement data.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".