Spacecraft Propulsion Using Angular Momentum Transfer Based on Gravity Gradient Effects
Bibliographic record
Abstract
Typical spacecraft propulsion systems depend upon the transfer of linear momentum through the expulsion of propellant using rocket motors or ion thrusters. This paper presents a method of spacecraft propulsion in which rotational angular momentum is transferred to orbital angular momentum due to the influence of gravity gradient effects. By applying torque to maintain a specific orientation with respect to the gravity gradient, the spacecraft orbital angular momentum is increased or decreased. If momentum wheels or control moment gyroscopes are used, no propellant is required and orbital maneuvers may be performed using solely electrical power. The equations of motion are presented along with analysis of the resulting change in orbital elements, demonstrating the relationship between spacecraft orientation and effective propulsive thrust. Simulation of the equations of motion is used to demonstrate the performance of the proposed technique and is verified by comparing results using both Lagrange dynamics and Newton–Euler dynamics. Although the resulting effects of this approach are small in comparison with conventional propulsion methods, it may be useful in applications such as exploration of asteroids and small moons, deorbiting of decommissioned satellites, or simply to reduce the requirements of a primary propulsion system.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".