Probabilistically optimum design of frame structure

Author(s):  
Y. Murotsu ◽  
M. Kishi ◽  
H. Okada ◽  
M. Yonezawa ◽  
K. Taguchi
1984 ◽  
Vol 1984 (155) ◽  
pp. 198-206
Author(s):  
Mitsuo Kishi ◽  
Hiroo Okada ◽  
Yoshisada Murotsu ◽  
Katashi Taguchi

2019 ◽  
Vol 9 (24) ◽  
pp. 5486 ◽  
Author(s):  
Shuang Li ◽  
Jintao Zhang

The study proposes a retrofitting method with an optimum design of viscous dampers in order to improve the structural resistant capacity to earthquakes. The retrofitting method firstly uses a 2D frame model and places the viscous dampers in the structure to satisfy the performance requirements under code-specific design earthquake intensities and then performs an optimum design to increase the structural collapse-resistant capacity. The failure pattern analysis and fragility analysis show that the optimum design leads to better performance than the original frame structure. For regular structures, it is demonstrated that the optimum pattern of viscous damper placement obtained from a 2D frame model can be directly used in the retrofitting of the 3D frame model. The economic loss and repair time analyses are conducted for the retrofitted frame structure under different earthquake intensities, including the frequent earthquake, the occasional earthquake, and the rare earthquake. Although the proposed method is based on time-history analyses, it seems that the computational cost is acceptable because the 2D frame model is adopted to determine the optimum pattern of viscous damper placement; meanwhile, the owner can clearly know the economic benefits of the retrofitting under different earthquake intensities. The retrofitting also causes the frame to have reduced environmental problems (such as carbon emission) compared to the original frame in the repair process after a rare earthquake happens.


2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
S. Talatahari ◽  
E. Khalili ◽  
S. M. Alavizadeh

Accelerated particle swarm optimization (APSO) is developed for finding optimum design of frame structures. APSO shows some extra advantages in convergence for global search. The modifications on standard PSO effectively accelerate the convergence rate of the algorithm and improve the performance of the algorithm in finding better optimum solutions. The performance of the APSO algorithm is also validated by solving two frame structure problems.


Author(s):  
Wenzhong Zhao ◽  
Shapour Azarm

Abstract In this paper, a new method for optimum design of frame structures is presented. The method is based on a hierarchical decomposition of the structure into two-levels, namely, the bottom- and the top-level. The bottom-level consists of several subproblems each dealing with the cross-sectional sizing of a given frame-element. The top-level consists of one subproblem which is formulated for configuration design of the frame structure. Since there may be a large number of frame elements, a new shape multiplier method has been developed to simplify the formulation of the bottom-level subproblems. Furthermore, a two-level solution procedure has been developed which first solves the bottom-level subproblems based on their monotonicity analysis. It then solves the top-level subproblem as it coordinates, based on a linear approximation, the solutions to the bottom-level subproblems. Three examples with increasing degree of difficulty are presented to demonstrate the effectiveness of the method.


1993 ◽  
Vol 115 (1) ◽  
pp. 132-142 ◽  
Author(s):  
Wenzhong Zhao ◽  
Shapour Azarm

In this paper, a new method for optimum design of frame structures is presented. The method is based on a hierarchical decomposition of the structure into two-levels, namely, the bottom- and the top-level. The bottom-level consists of several subproblems each dealing with the cross-sectional sizing of a given frame-element. The top-level consists of one subproblem which is formulated for configuration design of the frame structure. Since there may be a large number of frame elements, a new shape multiplier method has been developed to simplify the formulation of the bottom-level subproblems. Furthermore, a two-level solution procedure has been developed which first solves the bottom-level subproblems based on their monotonicity analysis. It then solves the top-level subproblem as it coordinates, based on a linear approximation, the solutions to the bottom-level subproblems. Three examples with increasing degree of difficulty are presented to demonstrate the effectiveness of the method.


2016 ◽  
Vol 19 (3) ◽  
pp. 37-42 ◽  
Author(s):  
M. Fridman ◽  
Keyword(s):  

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