This study investigated the self-sensing behavior of nonconductive glass fiber reinforced polymer (GFRP) reinforced concrete beam incorporated with electrostatic self-assembly carbon nanotube-nano carbon black (CNT-NCB) composite fillers (CNCFs) under monotonic… Click to show full abstract
This study investigated the self-sensing behavior of nonconductive glass fiber reinforced polymer (GFRP) reinforced concrete beam incorporated with electrostatic self-assembly carbon nanotube-nano carbon black (CNT-NCB) composite fillers (CNCFs) under monotonic and cyclic flexural loadings. The CNCFs feature synergistic effect of long-range conduction for fibrous CNTs and short-range conduction for granular NCBs, as well as their good dispersibility. Self-sensing signals in the compression and tension zones of the concrete beams were synchronously recorded through embedding stainless steel gauze electrodes in these sensing zones. Experimental results showed that incorporating CNCFs can achieve low and stable electrical resistivity (ranging from 33 to 76 Ω‧cm) for the concrete beams. Under monotonic flexural loading, the largest resistivity variation was observed in the case of concrete beam with 1.8 vol.% CNCFs, and the magnitude of fractional changes in resistivity (FCR) reached nearly 286%. Moreover, FCR in tension zone was more pronounced than that in compression zone. Under cyclic flexural loading, high self-sensing repeatability and stability of FCR variation with strain were obtained for all the concrete beams, and concrete beam with 2.0 vol.% CNCFs demonstrated the optimum self-sensing capability for its highest strain sensitivity of 322.7. Consequently, by measuring FCR of concrete beams with CNCFs and replacing metallic steel reinforcement with nonconductive GFRP bars which have the benefits of avoiding short circuit or electric field disturbance inside self-sensing concrete, in-situ monitoring the strain and damage accumulation of concrete components can be achieved.
               
Click one of the above tabs to view related content.