Investigating the ride properties of a particle filled wheel for planetary mobility
Bibliographic record
Abstract
Ride is the isolation of passenger and cargo from terrain inputs on a movingvehicle. While most lunar rover designs assign this duty to shock absorbers, DrPeter Radziszewski and Dr Sudarshan Martins propose it be supplied in largerpart by the wheels. Their invention, dubbed iRings, consists of a 24 inch diameterchainmail tire carcass filled with thousands of polypropylene spheres. When spunbeyond a critical speed, their centripetal acceleration compresses them against thechain-mail, which lacking any structure, adopts their bulk stiffness, damping andshape. In this thesis, measurements of iRings' free response to an impulse whilespinning are analysed to create a linear single degree of freedom contact model.The model's damping ratio drops from 0.8-0.9 at 0 rpm to 0.01 at 131 rpm as bothits stiffness and damping decrease with speed. The transition occurs close to theDavis critical speed of 54 rpm. Throughout, natural frequency remains constantat 3-4 Hz despite large fluctuations in stiffness. This is likely because iRingsoscillates as a result of plastic and not elastic deformation. This model is matchedin-silico to the Canadian Space Agency's (CSA) rovers Juno and Artemis and thewhole is tested on a sinusoidal lunar analogue terrain supplied by the CSA. TheiRings wheel is found to supply comparable, but slightly inferior isolation thana pneumatic tire, the Carlisle AT-489. Nevertheless, iRings proves itself to be apassively adaptive suspension component and with improvements to its stiffness,could surpass the pneumatic wheel.
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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 | 0.000 |
| 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) | 0.002 | 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".