Spatial Parameterization of Blunt Body Dynamics under Parachutes
Bibliographic record
Abstract
The dynamics of blunt bodies under parachutes is complex. The designer must balance translational requirements to slow down rapidly and over short distance, without violating rotational requirements to avoid high rates, flipover, and riser recontact. The designer’s effectors are: parachute drag area, the timing of reefing stages, timing of chute cutaway, and timing of next stage deployment. In the time domain, the equations of motion are non-linear and time varying, which has limited their solution to the most idealized cases, among them the steady state flight at constant dynamic pressure. The steady state dynamic pressure assumption is quite limiting as the whole purpose of parachutes is to reduce the dynamic pressure in a series of highly transient events. This paper explores the body/chute system dynamics with distance as an independent variable, rather than time. We find in the spatial coordinates, the differential equation for dynamic pressure becomes linear and yields a simple closed form solution. But the main finding here is that translational dynamics alter the rotational stability during the velocity transient period. This effect is a strong function of the difference in drag area between the previous stage and the next, and decays to zero as the system approaches steady state velocity. The transient term is found to be stabilizing at cutaway (reducing drag area) and destabilizing for reefed systems (increasing drag area).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".