Preliminary design of a revolute to prismatic morphing compliant joint
Bibliographic record
Abstract
The reduction of weight and size of mechanisms are important and difficult challenges considering portability, energy efficiency, and simplicity of fabrication. One of the solutions to address these issues consists of mechanisms with variable topology for which the mobility of the output is a succession of several simpler elementary motions. This change of mobility allows for achieving complex motions without necessitating a complicated design where many actuators or types of mechanical transmissions are required. Indeed, these variable topology mechanisms, also referred to as morphing mechanisms, have the ability to change their output motion throughout their workspace. Hand tools, medical devices, and aerospace robotic end-effectors are potential applications of this technology. In this paper, conceptual designs of such a revolute to prismatic morphing joint and its implementation using compliant hinges are proposed. Additionally, performance indexes pertaining to the desired output motion are proposed. First, a pseudo-rigid body model of a design candidate is presented, and simulations of this model are compared with finite element analyses to ensure accuracy. Then, several design features are quantitatively evaluated to propose improvements for future versions of the design. Finally, an early prototype illustrates the potential and feasibility of the proposed design as well as a possible application. Video
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.
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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".