Analytical approach for crack identification of glass fiber reinforced polymer–sea sand concrete composite structures based on strain dissipations

Abstract

Glass fiber reinforced polymer bars have potential application in the seawater sea sand concrete. In this study, an analytical method was proposed to examine the internal crack development in glass fiber reinforced polymer–sea sand concrete composites. The method was derived by analyzing the strain dissipation and shear-lag behavior. Thus, the internal cracks can be quantitatively identified by the proposed model with Fourier transform analysis. The proposed approach was experimentally verified through pullout tests for the specimens with artificial cracks. The results indicated that the prediction errors were less than 10%. In addition, the piezoelectric sensors were adopted to verify the proposed model. A damage index ( DI) defined by the energy loss of received signals was used to characterize cracks inside the composite. Loading test results indicated that the DI-calculated cracks were consistent with the proposed analytical model. Finally, the cyclic loading tests of the glass fiber reinforced polymer composite were conducted using both strain gauges and PZT sensors. The results have shown that the differences between the proposed approach and PZT sensors were less than 15%. Thus, the proposed approach in this study could provide an alternative approach for quantitative evaluation of internal cracks in the glass fiber reinforced polymer–coral sand–cement composites.

Effect of particle breakage on the shear strength of calcareous sands

“…This phenomenon has been recognized as one of the most important features of calcareous sands, which is closely related to the strength, deformation and permeability of calcareous sands (David et al 2011;Shahnazari and Rezvani 2013). In fact, the dynamic breakage of calcareous sands has been widely observed in some engineering practices (Coop et al 2004, Fukuoka et al 2007, Hardin 1985, Hyodo et al 2002, Lade et al 1996, Miao and Airey 2013, Pfleiderer et al 2006, Wu et al 2014, Yu 2017, Xu et al 2020a. It usually occurs when the shear stress exceeds the shear strength of sands, especially for the poorly graded samples (Bolton et al 2008).…”

Machine-Learning-Aided Prediction of Flexural Strength and ASR Expansion for Waste Glass Cementitious Composite

“…The ASR expansion was 0.0654% for 30% WGP samples activated by 2% Na 2 SO 4 and 2% alkali, which was 54% smaller than that of specimen 75G30. This might be because the alkaline activator increased the concentration of calcium ions, thus generating fewer swelling gels [66,73]. Regarding the chemical activator's content, the relationship between it and ASR expansion was not obvious, and therefore, ML models were proposed, as discussed in the next section.…”

Health Monitoring System with Hybrid Laser Sensor Networks and Cloud Computing for Subway Tunnels

“…After the ranging was finished, the laser rangefinder entered the sleep mode, until the next time it was activated. Using the tunnel intelligent monitoring and acquisition system, according to the layout shown in Figure 10(b), multiple infrared laser rangefinders, pull-wire convergence meters, and measurement targets were arranged at key sections of the tunnel [33,34]. According to the initial installation parameters and the initial ranging readings of each instrument, a spatial coordinate system was established, and the initial coordinates of each point was recorded.…”