An advanced form-finding of tensegrity structures aided with noise-tolerant zeroing neural network

2022 ◽  
Author(s):  
Zhongbo Sun ◽  
Liming Zhao ◽  
Keping Liu ◽  
Long Jin ◽  
Junzhi Yu ◽  
...  
Keyword(s):  
Neural Network ◽  
Form Finding ◽  
Tensegrity Structures ◽  
Advanced Form ◽  
Noise Tolerant

Advanced form-finding of tensegrity structures

2010 ◽  
Vol 88 (3-4) ◽  
pp. 237-246 ◽  
Author(s):  
Hoang Chi Tran ◽  
Jaehong Lee
Keyword(s):  
Form Finding ◽  
Tensegrity Structures ◽  
Advanced Form

scholarly journals Form-Finding of Tensegrity Model with Triangular Cells

2018 ◽  
Vol 7 (3.36) ◽  
pp. 137
Author(s):  
Nur Farizah Filzah Naing ◽  
Oh Chai Lian ◽  
Ilyani Akmar Abu Bakar ◽  
Mohd Raizamzamani Md Zain
Keyword(s):  
Inverse Method ◽  
Equilibrium Equations ◽  
Form Finding ◽  
Tensegrity Structures ◽  
Weight Structure ◽  
Tensegrity Model ◽  
Generalized Inverse Method ◽  
Stage Class ◽  
System Of Equilibrium Equations ◽  
Finding Method

Tensegrity structures is a light-weight structure compared to concrete structures that are heavy and rigid in shape. The studies on form-finding for tensegrity configuration are still ongoing and have been extensively conducted. Additionally, many proposed tensegrity structures have not been built for real applications. This study aims to determine potential self-equilibrated configurations of three-stage Class I tensegrity model assemblage with triangular cells, which may be applied as deployable towers. The form-finding methodology involves phases in establishment of desired form and formulation for the self-equilibrated state. The system of equilibrium equations was solved by Moore-Penrose generalized inverse method.  A range of twist angles 10o – 50o for triangular cells was investigated in the form-finding process.  It was found that the form-finding method via changing of twist angles has successfully search self-equilibrated tensegrity models.  

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