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Design and parameter optimization of a biomimetic jellyfish origami mechanism (BJOM) based on waterbomb tessellations.
- Source :
-
Mechanism & Machine Theory . Jun2023, Vol. 184, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
-
Abstract
- • A biomimetic jellyfish origami mechanism (BJOM) based on waterbomb is designed. • The kinematics model of the BJOM is established. • The optimization models of the BJOM are established and analyzed. • Fabrication and experimental testing of BJOM prototype is also performed. In this paper, a biomimetic jellyfish origami mechanism (BJOM) based on waterbomb tessellations is designed. Its geometric model is established, and its kinematic equation is derived. Its volume ratio and fineness ratio that characterize the morphological characteristics are analyzed. The maximum volume ratio and the maximum fineness ratio range were taken as the two optimization objectives, respectively. And two independent single-objective optimization models were established to optimize the structural parameters of the BJOM. Compared with the example before optimization, the results of the two optimization models have greatly improved the range of fineness ratio and the volume ratio. Finally, three factors about fineness ratio, volume ratio and material consumption were comprehensively considered to establish a three-objective optimization model. The results of these three optimization models compared is shown: the BJOM after three-objective comprehensive optimization has better comprehensive performance than the former two optimization schemes. It shows the feasibility of the optimization method and the superiority of the optimization design. [ABSTRACT FROM AUTHOR]
- Subjects :
- *JELLYFISHES
*ORIGAMI
*GEOMETRIC modeling
*KINEMATICS
Subjects
Details
- Language :
- English
- ISSN :
- 0094114X
- Volume :
- 184
- Database :
- Academic Search Index
- Journal :
- Mechanism & Machine Theory
- Publication Type :
- Academic Journal
- Accession number :
- 162288648
- Full Text :
- https://doi.org/10.1016/j.mechmachtheory.2023.105291