Long-term reference attitude path planning for gravitational wave detection satellite in high geocentric orbit
Bibliographic record
Abstract
The solar panel of a space gravitational wave detection satellite is usually fixed on one side due to the working environment requirement of the payload. Hence, the pointing of the panel must be controlled by adjusting the satellite’s attitude. For space gravitational wave detection satellites in high earth orbit, the light conditions are constantly changing with the Earth’s revolution around the sun, so when the light conditions of the panel are insufficient, the satellite must suspend the science mode of gravitational wave detection and enter the non-science mode to adjust the attitude and ensure the satellite energy supply. This paper develops a segmentation attitude planning scheme for the long-term attitude path planning of the non-science mode while considering the solar panel’s power supply efficiency and the satellite’s fuel consumption. Specifically, the non-science mode is divided into several segments, and a multi-segment attitude hold replaces the long-term attitude maneuver of tracking the sun. The satellite is maintained at a constant attitude relative to the inertial system within each segment while satisfying the angle requirement between the sun vector and the panel. Then, for the attitude maneuver between each segment, the reference attitude path is obtained using the Gauss pseudospectral method with the objective of minimum fuel consumption while considering multiple constraints. Through numerical simulations, the results demonstrate that the segmentation attitude planning scheme ensures the light conditions of the solar panel and reduces fuel consumption by about 35% compared with the scheme of tracking the sun.
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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".