๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Analysis of clustered tensegrity structures using a modified dynamic relaxation algorithm

โœ Scribed by Nizar Bel Hadj Ali; Landolf Rhode-Barbarigos; Ian F.C. Smith


Publisher
Elsevier Science
Year
2011
Tongue
English
Weight
797 KB
Volume
48
Category
Article
ISSN
0020-7683

No coin nor oath required. For personal study only.

โœฆ Synopsis


Tensegrities are spatial, reticulated and lightweight structures that are increasingly investigated as structural solutions for active and deployable structures. Tensegrity systems are composed only of axially loaded elements and this provides opportunities for actuation and deployment through changing element lengths. In cable-based actuation strategies, the deficiency of having to control too many cable elements can be overcome by connecting several cables. However, clustering active cables significantly changes the mechanics of classical tensegrity structures. Challenges emerge for structural analysis, control and actuation. In this paper, a modified dynamic relaxation (DR) algorithm is presented for static analysis and form-finding. The method is extended to accommodate clustered tensegrity structures. The applicability of the modified DR to this type of structure is demonstrated. Furthermore, the performance of the proposed method is compared with that of a transient stiffness method. Results obtained from two numerical examples show that the values predicted by the DR method are in a good agreement with those generated by the transient stiffness method. Finally it is shown that the DR method scales up to larger structures more efficiently.


๐Ÿ“œ SIMILAR VOLUMES


Geometry optimizations of benzene cluste
โœ Cai Wen-Sheng; Yu Fang; Shao Xue-Guang; Pan Zhong-Xiao ๐Ÿ“‚ Article ๐Ÿ“… 2010 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 399 KB ๐Ÿ‘ 1 views

## Abstract A modified genetic algorithm with realโ€number coding, nonโ€uniform mutation and arithmetical crossover operators was described in this paper. A local minimization was used to improve the final solution obtained by the genetic algorithm. Using the expโ€6โ€“1 interatomic energy function, the

Numerical stability of dynamic relaxatio
โœ A. C. Cassell; R. E. Hobbs ๐Ÿ“‚ Article ๐Ÿ“… 1976 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 201 KB

## Abstract The estimation of the parameters (โ€˜fictitious densitiesโ€™) which control the convergence and numerical stability of a nonโ€linear Dynamic Relaxation solution is described. The optimal values of these parameters vary during the iterative solution and they are predicted from the Gerschgรถrin

On the optimum design of cluster structu
โœ Honglan Jin; Yoshikazu Miyanaga; Koji Tochinai ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 164 KB ๐Ÿ‘ 2 views

In discussing self-organizing neural networks, to some extent a large-scale network is assumed in order to achieve generality and adaptability. This paper discusses an optimal structurization method for a nonlinear network, based on a self-organizing algorithm with a two-layer structure. The basic s