Optimal Design of Double-Layer Barrel Vault Space Structures

Author(s):  
Ali Kaveh ◽  
Majid Ilchi Ghazaan
2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Reza Kamyab Moghadas ◽  
Kok Keong Choong ◽  
Sabarudin Bin Mohd

The main aim of the present work is to determine the optimal design and maximum deflection of double layer grids spending low computational cost using neural networks. The design variables of the optimization problem are cross-sectional area of the elements as well as the length of the span and height of the structures. In this paper, a number of double layer grids with various random values of length and height are selected and optimized by simultaneous perturbation stochastic approximation algorithm. Then, radial basis function (RBF) and generalized regression (GR) neural networks are trained to predict the optimal design and maximum deflection of the structures. The numerical results demonstrate the efficiency of the proposed methodology.


1993 ◽  
pp. 1: 563-572 ◽  
Author(s):  
J. Estevez ◽  
J. Pablos ◽  
S. Muniz ◽  
M. Freire ◽  
R. Vazquez ◽  
...  

2020 ◽  
Vol 40 (16) ◽  
pp. 1605001
Author(s):  
毛珊 Mao Shan ◽  
解娜 Xie Na ◽  
赵建林 Zhao Jianlin

2018 ◽  
Vol 33 (3-4) ◽  
pp. 115-123
Author(s):  
Ali Kaveh ◽  
Majid Ilchi Ghazaan ◽  
Soroush Mahjoubi

Barrel vaults are effective semi-cylindrical forms of roof systems that are widespread for multipurpose facilities including warehouse, rail station, pools, sports center, airplane hungers, and community centers because of providing long-span and economical roof with significant amount of space underneath. In the present study, size optimization of double-layer barrel vaults with different configurations is studied. Four recently developed algorithms consisting of the CBO, ECBO, VPS, and MDVC-UVPS are employed and their performances are compared. The structures are subjected to stress, stability, and displacement limitations according to the provisions of AISC-ASD. The design variables are the cross-sectional areas of the bar elements which are selected from steel pipe sections. The numerical results indicate that the MDVC-UVPS outperforms the other algorithms in finding optimal design in all examples.


2016 ◽  
Vol 58 (6) ◽  
pp. 1109-1126 ◽  
Author(s):  
Saeed Gholizadeh ◽  
Changiz Gheyratmand ◽  
Hamed Davoudi

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