A compliant-mechanism-based lockable prismatic joint for high-load morphing structures
Bibliographic record
Abstract
Lockable joints are widely used in robotic systems and adaptive structures for energy management and/or topology reconfiguration. However, it is still challenging to design a joint with desired properties, including high locking load, infinite locking positions, short switching time, energy-efficient control, and a compact and lightweight structure. This paper aims at this open problem by presenting a novel piezoelectric (PZT) actuated lockable prismatic joint. This joint is a compliant mechanism (CM) consisting of a compound bridge-type compliant mechanism (CBCM) and a pair of compound multibeam parallelogram mechanisms (CMPMs). It can produce the required input/output stiffness to transmit large forces for high-load locking. It can also provide a desired input/output motion range for PZT actuation-based unlocking and for facilitating preloading adjustment. An analytical model is presented based on a compliance matrix method and the nonlinear model of the CMPM to predict the joint's static characteristics under various input/output conditions. A two-step optimization framework is proposed for locking applications. The theoretical study and nonlinear FEA/experimental verification confirm the feasibility of the design and the accuracy of the proposed model.
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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) | 0.001 | 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".