Experimental investigation of the behavior of concrete‐filled high‐strength glass fiber‐reinforced polymer tubes under static and cyclic axial compression

Abstract

This experimental study investigated the load–displacement behavior, ultimate strength, and failure modes of hollow and concrete‐filled high‐strength glass fiber‐reinforced polymer (GFRP) tubes under static and cyclic axial compression. For this purpose, pultruded GFRP tubes were used which contained fibers oriented at 0°, +45°, and −45° to the longitudinal axes of the tubes. Self‐compacting concrete (SCC) was used for in‐filling the hollow GFRP tubes. The main parameters considered in the test program were the tube cross‐section, column length, and cyclic loading range. A total of 28 specimens of lengths equal to either 0.5 or 1.5 m were tested under static and cyclic axial compressive loading. The experimentally obtained load–displacement and load‐axial/hoop strain behaviors are discussed in this paper. It was verified that in‐filling the GFRP tubes with concrete can enhance their axial strength and stiffness, though it is not able to prevent the brittle nature of the failure. Hollow GFRP tubes displayed linear‐elastic behavior with a constant axial stiffness up to failure under both static and cyclic loading, while the concrete‐filled specimens exhibited a bilinear load–displacement behavior with the change in stiffness occurring at the point at which the GFRP tube starts to act as a confining jacket. Under cyclic loading, the concrete‐filled specimens suffered degradation in axial stiffness with the rate of deterioration decreasing with increasing number of cycles. However, a consistent relationship between the cyclic load range magnitude and number of cycles to failure could not be found using the experimentally obtained data.

A Governance Framework to Assist with the Adoption of Sensing Technologies in Construction

“…FGB technology present great benefits on monitoring the quality of concrete [ 88 , 89 , 90 ]. Sensing technologies also invite digital technologies and artificial intelligence into the construction industry to predict the mechanical properties under static and flexural fatigue loading [ 91 , 92 , 93 ]. Forty references related to motivations were detected in fourteen interviews and assigned to eight nodes.…”

Mechanical Performance Prediction for Sustainable High-Strength Concrete Using Bio-Inspired Neural Network

“…The respective sensitivity response of each input variable is calculated by Equation (10). Afterward, the relative importance of each variable is calculated by Equation (11).…”

“…HSC has been widely applied in long-span bridges because it sustains superior dead and live loading with fewer bridge piers and thus prolongs the service lifespan [7][8][9]. Meanwhile, HSC is also promising in high buildings because it enables oversized columns to yield more floor space and larger column spacing without detracting from lower floors [10][11][12]. The behaviour of connectors when embedded in the HSC, such as the shear resistance and ductility, has been investigated by several researchers [13,14].…”

Research on the safety assessment of RC workshop buildings in earthquake site based on the fuzzy comprehensive evaluation

“…The indexes of highperformance concrete are often better than those of ordinary concrete. [36][37][38][39][40][41] Therefore, if the high-performance concrete is used to column, earthquake damage to the column will be greatly reduced. Taking the workshop column and the plaster layer as an example, the detail categories and the corresponding detail seismic damage descriptions are shown in Table 1.…”

“…In general, the column is made of normal concrete rather than high‐performance concrete. The indexes of high‐performance concrete are often better than those of ordinary concrete 36–41 . Therefore, if the high‐performance concrete is used to column, earthquake damage to the column will be greatly reduced.…”