Design and Evaluation of a Semi-Empirical Piece-wise Exponential Atmospheric Density Model for CubeSat Applications
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents the theory and design of a semi-empirical atmospheric density model based on data from the MSIS-86 model. Created as part of ongoing research into optimal guidance laws for nanosatellite applications, this model focuses on being computationally lightweight, while providing reasonably accurate atmospheric density predictions at geometric altitudes ranging from 0 - 1000 km. The model is validated against data from existing analytical and empirical atmospheric models. It is then implemented in a variety of orbit and attitude propagation environments in Matlab-Simulink to assess its stability, validity, and computational footprint. The orbital elements from each simulation were compared against those obtained from baseline simulations run using the Naval Research Lab (NRL) MSISE-00 model. The results show good agreement with the baseline simulations, while indicating a signicant reduction in computational run time.
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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 | 0.000 |
| 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) | 0.000 | 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 it