Certain Investigations on Soft Lander for Lunar Exploration
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
As all expeditions on moon are of great importance and people are more curious to know more and more about it, a lunar module is required to carry instruments safely to lunar surface. The lunar module has to be landed on its legs and with minimal shock on all kinds of surface after being dropped from a height, be it a hard or soft surface. So simulations and experiments on lunar landers are indispensable for a successful launch. Based on a model of the lunar lander, a CAD model was designed using SolidWorks and was tested for kinematics, dynamics by simulating its free fall using ADAMS. With the insight gained, a scaled physical model of the lander was fabricated with two-wheeler rear wheel spring-dampers in primary struts and packaging foam in footpads as cost-effective shock absorbing mechanisms. With a focus on impact forces on footpads, being one of the most important parameters, interfacing Arduino-UNO-Wifi-board with load cells a force measurement and wireless data acquisition system was developed, calibrated and incorporated into the footpads. Drop test experiments and simulations were carried out for different drop heights and angles of landing surface and the impact forces on the footpads and soil penetration depths were measured, and a basic shock and energy analysis was carried out. Our results indicate that shocks are within limits up to a certain height and landings are stable for the anticipated landing surface angles for the chosen model parameters and surface conditions.
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 | 0.001 |
| 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