DAVINCI Venus Entry, Descent, and Landing Modeling and Simulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2023-1165.vid The Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging (DAVINCI) mission is scheduled to launch in June 2029 and explore Venus via two flybys and a probe descent scheduled for June 2031. The goals of the mission are to study the origin, evolution, and current state of Venus and to understand if it was habitable at a point in the past. The entry, descent, and landing (EDL) concept of operations of the probe leverages on the successful Pioneer Venus large probe mission. The science objectives of the mission levy certain requirements on the EDL system, such as landing in the scientifically important Alpha Regio Tessera and telemetering several gigabytes of instrumentation data to the orbiting relay spacecraft before the probe impacts the surface. In order to optimize the EDL sequence of the lander and to verify key driving requirements, a six degree of freedom EDL flight mechanics simulation has been created based on the best available aerodynamic and atmospheric models for Venus. This paper describes the EDL modeling and simulation and summarizes the current flight mechanics results for the mission.
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.
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