The technology of piezoceramic based smart aggregates (SAs) has demonstrated its potential in the comprehensive monitoring of concrete structures. However, its usage in the moisture monitoring of concrete structures has not yet been explored. In this research, SA transducers are used to detect the degree of water infiltration in concrete components and an active sensing method is proposed for moisture monitoring. For experimental study and verification, two short plain concrete columns, with embedded SAs, were fabricated, and an apparatus was developed to perform moisture monitoring of these two columns under different moisture conditions. Data were analyzed to study the relationship between the depth of water seepage and the sensing indicators of receiving signals. Experimental results show that the sensing indicators are very sensitive to the degree of water infiltration inside the column. These sensing indicators show a decreasing trend with increasing depth of water seepage, and this leads to the promising conclusion that these parameters can be used as evaluation indices for the water seepage monitoring of concrete structures.

Fracture networks play a more significant role in conducting fluid flow and solute transport in fractured rock masses, comparing with that of the rock matrix. Accurate estimation of the permeability of fracture networks would help researchers and engineers better assess the performance of projects associated with fluid flow in fractured rock masses. This study provides a review of previous works that have focused on the estimation of equivalent permeability of twodimensional (2-D) discrete fracture networks (DFNs) considering the influences of geometric properties of fractured rock masses. Mathematical expressions for the effects of nine important parameters that significantly impact on the equivalent permeability of DFNs are summarized, including (1) fracturelength distribution, (2) aperture distribution, (3) fracture surface roughness, (4) fracture dead-end, (5) number of intersections, (6) hydraulic gradient, (7) boundary stress, (8) anisotropy, and (9) scale. Recent developments of 3-D fracture networks are briefly reviewed to underline the importance of utilizing 3-D models in future research.

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