Concrete is one of the most common materials used to construct a variety of civil infrastructures. However, since con-crete is susceptible to fractures, it is essential to confirm the strength development of concrete during the curing process, in order to prevent unexpected collapse. To address this issue, this study proposes an artificial neural network (ANN)-based strength estimation technique using several kinds of strength related factors of concrete materials. In particular, the variations in mechanical properties of concrete were measured through electro-mechanical impedance (EMI) change using an embedded piezoelectric sensor. The ANN was trained to estimate the strength of concrete by using watercement ratio, curing time and temperature, maturity from internal temperature, and 1-CC of the EMI signals. The trained ANN was verified with conventional strength estimation models throughout a series of experimental studies. According to the comparison results, it is noted that the proposed technique could be very effectively applied to estimate the strength of concrete.
The relationship among air permeability, pressure, and pore size from a viscous- to a molecular-flow region is not well understood. In this work, air permeability in a straight circular pipe was studied considering viscous and molecular flows. I learned that the air-permeability coefficient and intrinsic air-permeability coefficient exhibit contrasting pressure dependence: that of the air-permeability coefficient is larger in a larger pore, whereas that of the intrinsic air-permeability coefficient is larger in a smaller pore. I thus proposed a method to obtain the air-permeability coefficient at atmospheric pressure from that measured under vacuum or pressurised condition. From the Reynolds number study, turbulent flow study is unnecessary in air flow in concrete.
In order to better understand the failure mechanism of recycled aggregate concrete (RAC), numerical studies on modeled recycled aggregate concrete (MRAC) were conducted to investigate the initiation and propagation of microcracks and stress-strain responses of RAC. The constitutive relationships of interfacial transition zones (ITZs) and the corresponding cement mortars were proposed with plastic-damage constitutive relationships. The mechanical properties and the thickness of ITZs were obtained using advanced nanoindentation. The effects of the relative properties between new and old cement mortars on the failure process and stress-strain responses of MRAC were investigated. It was found that the numerical results agreed with the experimental results in terms of crack pattern and stress-strain curves under compression. The results showed that the microcracks first appeared around the weak new and old ITZs, and then propagated into the new and old cement mortar regions. With the increase of the relative strength between new and old cement mortars, the mechanical strengths of MRAC increased, and the microcracks initiation and propagation shifted from the new ITZ to the old ITZ. Overall, the numerical results indicated that optimizing the mix design and improving the properties of ITZs can be effective methods to enhance the mechanical properties of RAC.
In marine environments, deterioration of concrete infrastructures under airborne chloride attack is a common problem, which raises the need for a reliable prediction model of airborne chloride penetration into concrete structures to evaluate the service life of concrete structures. This study proposes a time-dependent computational model for predicting the amount of airborne chloride ingress into concrete under actual environmental conditions. The proposed model calculates the amount of chloride penetration by considering the amount of advection and diffusion of airborne chloride on the concrete surface. To compute the amount of airborne chloride penetration, the proportion of dry and wet sections on the concrete surface is assumed, and to ensure accurate prediction of chloride penetration into concrete structures under actual environment conditions, the washout effect of rainfall is taken into account in the calculation. The proposed model was verified through comparison of the experimental and on-site measurement results.