Rectangular Filament-Wound Glass Fiber Reinforced Polymer Tubes Filled with Concrete under Flexural and Axial Loading: Analytical Modeling

2005 ◽  
Vol 9 (1) ◽  
pp. 34-43 ◽  
Author(s):  
Amir Fam ◽  
Siddhwartha Mandal ◽  
Sami Rizkalla
2016 ◽  
Vol 20 (3) ◽  
pp. 374-393 ◽  
Author(s):  
Le Zhou ◽  
Lianguang Wang ◽  
Liang Zong ◽  
Gang Shi ◽  
Yunhao Bai ◽  
...  

Glass fiber–reinforced polymer tubes filled with steel-reinforced high-strength concrete are proposed as glass fiber–reinforced polymer–steel-reinforced high-strength concrete composite members. Eccentric compression is a typical loading scenario for such column members in practice. Experimental investigation on eight glass fiber–reinforced polymer tubes filled with steel–reinforced high-strength concrete columns subjected to eccentric compression was conducted. The effects of fiber orientation, thickness of glass fiber–reinforced polymer tube, slenderness ratio of columns, and loading eccentricity were investigated. It was found that the compression bearing capacity of glass fiber–reinforced polymer–steel-reinforced high-strength concrete columns increased with the decrease in the fiber tangle angle and the increase in the thickness of the glass fiber–reinforced polymer tube but reduced with the increase in the eccentricity and the slenderness ratio. Corresponding formulas were developed based on the nonlinear full-process analysis theory to describe the compression behavior of glass fiber–reinforced polymer–steel-reinforced high-strength concrete under eccentric loading. Good agreement was found through the comparison between the theoretical and the experimental results. The validated modeling approach was, therefore, employed to develop a parametric analysis that can be used to provide valuable guidance for practical application and further research on such structural members.


2010 ◽  
Vol 168-170 ◽  
pp. 143-151
Author(s):  
Hong Bo Guan ◽  
Qing Xiang Wang ◽  
Bing Feng Ruan

This paper presents the results of the experimental program and analytical modeling for performance evaluation of the eccentrically loaded composite short columns confined with Glass Fiber-Reinforced Polymer (GFRP) tube. This test matrix included six specimens, which were tested in the variable eccentricity. Research findings indicated that the strength of the concrete-filled GFRP tubular column was enhanced correspondingly; however, the strength gain caused by the GFRP tube decreased as the ratio of e/d0 was increased. A nonlinear analysis that accounts for the change in eccentricity caused by the lateral deformation was proposed to predict the columns’ strength. A comparison between analytical and experimental results of the present study demonstrated the accuracy and validity of the proposed analysis.


Machines ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 16
Author(s):  
Gabriel Mansour ◽  
Panagiotis Kyratsis ◽  
Apostolos Korlos ◽  
Dimitrios Tzetzis

There are numerous engineering applications where Glass Fiber Reinforced Polymer (GFRP) composite tubes are utilized, such as desalination plants, power transmission systems, and paper mill, as well as marine, industries. Some type of machining is required for those various applications either for joining or fitting procedures. Machining of GFRP has certain difficulties that may damage the tube itself because of fiber delamination and pull out, as well as matrix deboning. Additionally, short machining tool life may be encountered while the formation of powder like chips maybe relatively hazardous. The present paper investigates the effect of process parameters for surface roughness of glass fiber-reinforced polymer composite pipes manufactured using the filament winding process. Experiments were conducted based on the high-speed turning Computer Numerical Control (CNC) machine using Poly-Crystalline Diamond (PCD) tool. The process parameters considered were cutting speed, feed, and depth of cut. Mathematical models for the surface roughness were developed based on the experimental results, and Analysis of Variance (ANOVA) has been performed with a confidence level of 95% for validation of the models.


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