Adaptive structures and design concept of transformable joints
Bibliographic record
Abstract
This article describes the research framework for adaptive structures and the design concept of transformable joints. The research of adaptive structures can be splitted into different scales: deformation mechanisms (whole structure), cooperation mechanisms (inter-component) and actuation mechanisms (intra-component). This research will focus on transformable joints, which are based on special material properties (actuation) to accomplish the change of joint stiffness between locked and released states (transformation). Thereby, the control of DOF can be achieved, in order to finally realise the whole structure's form change (deformation). Alternatively under shock loads, the joints release and the structure occur certain deformation to dissipate energy and adjust to external loads. Afterwards, the structure recovers its original shape and removes residual strain through special/smart materials. Then the released joints relock again. By comparison of natural role models and adaptive structures, there are many similarities between them that we can learn from nature. In future research, e.g. adaptive stiffness, the experimental tests of potential materials and prototypes will be the main research methods. While for adaptive geometry, the knowledge of robotics, especially the part of geometric representations and transformations, will help to express this problem in mathematical way. This part will be mostly in conceptual level, so computer simulation will be used. The final goal of this research is to develop energy dissipation and shape-morphing strategies using transformable joints under varying loads as well as shock impact. These kinds of joints can not only be applied to tessellated shell structures, but also introduced to active facade systems.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".