123 Optimal Design of Flexible Structures utilizing Enumeration Algorithms for Rigid Framework
Bibliographic record
Abstract
An efficient approach for generating pin-jointed compliant mechanisms is presented. A compliant mechanism uses the elastic deformation of structural parts to realize the mechanism for shape transformation of the entire structure, which is contrary to the conventional link mechanism. Ohsaki and Nishiwaki (Struct. Multidisc. Optim., Vol.30, pp.327-334, 2005) presented a method for generating flexible multistable bar-joint mechanisms using nonlinear programming approach. However, due to highly nonlinear property of the problem, the nonlinear programming problem should be solved many times with random initial solutions to obtain several types of mechanisms. Since the compliant pin-jointed mechanism is usually statically determinate, the optimization problem can be solved easily if the design space is limited to statically determinate structures. Avis et al. (Proc. of COCOON 2006, LNCS 4112, pp.205-215, 2006) presented an algorithm for enumerating all the non-crossing generically minimally rigid bar-joint frameworks, which are regarded as statically determinate trusses in structural engineering. In this paper, bistable mechanisms utilizing snapthrough behavior are obtained more efficiently with the algorithm. In the numerical example, many types of bistable compliant mechanisms are generated.
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 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".