Study of Low Earth Orbit impact on ORCA2SAT subsystems
Bibliographic record
Abstract
Mission planning of CubeSats can be very challenging due to their mass, volume and power constraints. In addition, the majority of CubeSat projects are done at a University level, which can also mean constraints in terms of budget. In order to guarantee the mission’s success, several aspects must be studied prior to launch. Firstly, it must be assured that the satellite has enough accesses to the desired ground stations in order to establish communications while in orbit. However, to keep the satellite operational power generation is required. The profile of power generation varies throughout the year and is heavily dependent on the CubeSat’s orbit. Thus, it is crucial to assess the power generation for a long period in order to guarantee the operation of the satellite and help set limits for systems design and hardware selection. The constraints mentioned above make use of magnetorquers as the main attitude actuators, which require a study of the Earth’s magnetic field in order to compare the generated torques with the perturbative torques inherent to the space environment. Another concern are temperature limits of the components, therefore, the temperatures experienced by the satellite in orbit must be computed and decisions must be taken to allow for the mission’s success. As in the previous analysis, the dynamic behavior of the CubeSat under launch conditions can also draw the line between success and failure. This work describes the steps taken in order to simulate all the aforementioned aspects for the computed mission lifetime, in order to mitigate inherent risks and guarantee mission success for ORCA2Sat, a two unit Cube- Sat. The simulations were done through pertinent finite elements models and space environment computational models, for a deployment from the International Space Station. It was proved, with this comprehensive mission analysis, that for the studied critical factors ORCA2Sat’s mission can be accomplished for the desired period of time, keeping the satellite operational throughout its life in orbit.
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".