scholarly journals Experimental study and application of manufactured sand self-compacting concrete in concrete-filled-steel-tube arch bridge: A case study

2021 ◽  
Vol 15 ◽  
pp. e00718
Author(s):  
Wen-Qi Hou ◽  
Jia-Jun Yang ◽  
Zheng-Xin Zhang ◽  
Xiao-Qian Yuan
Keyword(s):  
Experimental Study ◽  
Steel Tube ◽  
Self Compacting Concrete ◽  
Arch Bridge ◽  
Concrete Filled Steel Tube ◽  
Manufactured Sand

scholarly journals Experimental Study of Self-Compacted Concrete-Filled Steel Tube (CFST) Truss Girders

2019 ◽  
Vol 12 (2) ◽  
pp. 98-104
Author(s):  
Marwa M. Thejeel ◽  
Muhaned A. Shallal
Keyword(s):  
Experimental Study ◽  
Flexural Strength ◽  
Failure Modes ◽  
Steel Tube ◽  
Design Equation ◽  
Self Compacting Concrete ◽  
Concrete Filled Steel Tube ◽  
Peak Loads ◽  
Steel Bar ◽  
The World

Concrete filled steel tube one of the most important modern innovations in the world. This paper studies the performance of steel tube truss girders filled with self-compacting concrete. Four CFST truss girders specimens tested. The first novelty in this research was using square tubes to made truss girder; the main parameters were bottom chord concrete compressive grade and reinforce steel bar is embedded in the bottom chord (second novelty). One bar with a nominal diameter 16 mm was used to reinforce the concrete in the bottom chord while keeping the concrete in the top chord without reinforced. This paper shows the load-displacement curves at the mid-span, deflections along the span, peak loads, flexural strength, and failure modes of the tested specimens. The design equation was used to predict the flexural strength of CFST truss specimens. Results show that the flexural strength increased with increasing the concrete grade from 29.23MPa to 48.41MPa by about 4.5% and increased by about 10.27% when using reinforce steel bar embedded the concrete in the bottom chord.

Preparation and Application of Self-Compacting Concrete-Filled Steel Tube Using Polymer Admixtures

2011 ◽  
Vol 415-417 ◽  
pp. 265-271
Author(s):  
Shang Jiang Chen ◽  
Xiao Ning Zhang
Keyword(s):  
Steel Tube ◽  
Mineral Admixture ◽  
Construction Technology ◽  
Self Compacting Concrete ◽  
Arch Bridge ◽  
Concrete Filled Steel Tube ◽  
Mix Proportion ◽  
Basic Parameters ◽  
Shrinkage Compensation ◽  
Preparation Techniques

Self-compacting concrete-filled steel tube is different from ordinary self-compacting concrete in many aspects. According to the demands of on-site construction conditions and construction technology of continuous pumping lift-up method for the project of Huaxi No.1 steel tube arch bridge, property requirements of self-compacting concrete filled steel tube were proposed in this paper. By using the preparation techniques such as optimization of basic parameters of concrete mix proportion, admixture composition and mineral admixture addition, self-compacting concrete filled steel tube was prepared with the properties such as initial slump more than 24cm, initial slump flow above 650mm, T50 between 5s and 15s, no slump loss for 4h, no bleeding, strength grade above C60 and shrinkage-compensation etc. It was applied in the steel tube arch bridge project successfully using the construction technology of pumping lift-up method.

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.

Investigation on the dynamic impact factor of a concrete filled steel tube butterfly arch bridge

2021 ◽  
pp. 113614
Author(s):  
Shiqiang Qin ◽  
Jiacheng Feng ◽  
Yun-Lai Zhou ◽  
Chao Li ◽  
Xuejin Huo ◽  
...  
Keyword(s):  
Impact Factor ◽  
Steel Tube ◽  
Dynamic Impact ◽  
Arch Bridge ◽  
Concrete Filled Steel Tube ◽  
Dynamic Impact Factor
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