Analysis of Flexible Joints for Micromachined Devices
Bibliographic record
Abstract
In micromachined devices, surface forces are often stronger than inertial forces. This is a serious disadvantage to conventional designs for prismatic and revolute joints in micromachines. Made from multiple pieces, conventional designs including a lot of sliding contact, which is a serious reliability concern due to stiction and wear problems. To eliminate the sliding contact, Fettig, Wylde, Hubbard, and Kujath investigated the use of compliant devices that closely mimic the behavior of traditional prismatic and revolute joints. In particular, they fabricated and tested a number of surface micromachined flexible joints. They were able to provide empirical data on the transverse, lateral, and rotational spring constants for the joints they fabricated. However, designers typically need to optimize device dimensions to meet their design requirements. To this end, the structures investigated by Fettig et al were analyzed. This paper will present expressions for predicting all three of the stiffness constants for the flexible joints.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".