scholarly journals A STUDY ON CONSTITUTIVE THEORY IN ELASTO-PLASTIC ANALYSIS USING ADDITIONAL LOAD : ANALYSIS OF CONCRETE FILLED-STEEL TUBE UNDER AXIAL COMPRESSION IN FINITE ELEMENT METHOD

1994 ◽  
Vol 59 (466) ◽  
pp. 69-77
Author(s):  
Junichiro ISHIDA
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Axial Compression ◽  
Steel Tube ◽  
Constitutive Theory ◽  
Concrete Filled Steel Tube ◽  
Additional Load ◽  
Plastic Analysis ◽  
Load Analysis ◽  
Element Method

Time-History Analysis of Seismic Response for the Concrete-Filled Steel Tubular Wind Turbine Tower Based on Finite Element Method

2010 ◽  
Vol 163-167 ◽  
pp. 2176-2180
Author(s):  
Yang Wen ◽  
Fei Zhou
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Wind Turbine ◽  
Time History ◽  
Steel Tube ◽  
Time History Analysis ◽  
Concrete Filled Steel Tube ◽  
Wind Turbine Tower ◽  
History Analysis ◽  
Element Method

In the article based on the geometric characteristics of the tower and force characteristics, the author designs the concrete-filled steel tube (CFST) 3 limbs column tower, and establishes finite element model of the tower. We carry on time history analysis of the concrete-filled steel tubular wind turbine tower based on finite element method when the earthquake wave is different. Under rare earthquake, the majority bars of the concrete-filled steel tube 3 limbs column tower are in the elastic stage, only a small number of bars in the top and the bottom are into the plastic phase. The post-seismic displacement at the top of tower is 1.1m which is slightly less than the tower height of 1 / 50 (1.26m) and meets the seismic requirements of the region. The analytical result may provide the foundational test data and advice for the design of the CFST wind turbine tower.

scholarly journals Artificial Neural Network-Based Method for Seismic Analysis of Concrete-Filled Steel Tube Arch Bridges

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zhen Liu ◽  
Shibo Zhang
Keyword(s):  
Neural Network ◽  
Finite Element Method ◽  
Artificial Neural Network ◽  
Finite Element ◽  
Seismic Analysis ◽  
Steel Tube ◽  
Arch Bridge ◽  
Concrete Filled Steel Tube ◽  
Cfst Arch Bridge ◽  
Artificial Neural

Seismic analysis of concrete-filled steel tube (CFST) arch bridge based on finite element method is a time-consuming work. Especially when uncertainty of material and structural parameters are involved, the computational requirements may exceed the computational power of high performance computers. In this paper, a seismic analysis method of CFST arch bridge based on artificial neural network is presented. The ANN is trained by these seismic damage and corresponding sample parameters based on finite element analysis. In order to obtain more efficient training samples, a uniform design method is used to select sample parameters. By comparing the damage probabilities under different seismic intensities, it is found that the damage probabilities of the neural network method and the finite element method are basically the same. The method based on ANN can save a lot of computing time.

Development of Multi-scale Plastic Analysis Code Based on Crystalline Homogenization Finite Element Method

2002 ◽  
Vol 2002.15 (0) ◽  
pp. 127-128
Author(s):  
Shinji IIHOSHI ◽  
Y. P. CHEN ◽  
Sei UEDA ◽  
Yasutomo UETSUJI ◽  
Eiji NAKAMACHI
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Multi Scale ◽  
Plastic Analysis ◽  
Element Method
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