Transport and retention of surfactant- and polymer-stabilized engineered silver nanoparticles in silicate-dominated aquifer material.

Packed column experiments were conducted to investigate the transport and blocking behavior of surfactant- and polymer-stabilized engineered silver nanoparticles (Ag-ENPs) in saturated natural aquifer media with varying content of material < 0.063 mm in diameter (silt and clay fraction), background solution chemistry, and flow velocity. Breakthrough curves for Ag-ENPs exhibited blocking behavior that frequently produced a delay in arrival time in comparison to a conservative tracer that was dependent on the physicochemical conditions, and then a rapid increase in the effluent concentration of Ag-ENPs. This breakthrough behavior was accurately described using one or two irreversible retention sites that accounted for Langmuirian blocking on one site. Simulated values for the total retention rate coefficient and the maximum solid phase concentration of Ag-ENPs increased with increasing solution ionic strength, cation valence, clay and silt content, decreasing flow velocity, and for polymer-instead of surfactant-stabilized Ag-ENPs. Increased Ag-ENP retention with ionic strength occurred because of compression of the double layer and lower magnitudes in the zeta potential, whereas lower velocities increased the residence time and decreased the hydrodynamics forces. Enhanced Ag-ENP interactions with cation valence and clay were attributed to the creation of cation bridging in the presence of Ca2+. The delay in breakthrough was always more pronounced for polymer-than surfactant-stabilized Ag-ENPs, because of differences in the properties of the stabilizing agents and the magnitude of their zeta-potential was lower. Our results clearly indicate that the long-term transport behavior of Ag-ENPs in natural, silicate dominated aquifer material will be strongly dependent on blocking behavior that changes with the physicochemical conditions and enhanced Ag-ENP transport may occur when retention sites are filled.

Kalman Filters in Geotechnical Monitoring of Ground Subsidence Using Data from MEMS Sensors.

The fast development of wireless sensor networks and MEMS make it possible to set up today real-time wireless geotechnical monitoring. To handle interferences and noises from the output data, Kalman filter can be selected as a method to achieve a more realistic estimate of the observations. In this paper, a one-day wireless measurement using accelerometers and inclinometers was deployed on top of a tunnel section under construction in order to monitor ground subsidence. The normal vectors of the sensors were firstly obtained with the help of rotation matrices, and then be projected to the plane of longitudinal section, by which the dip angles over time would be obtained via a trigonometric function. Finally, a centralized Kalman filter was applied to estimate the tilt angles of the sensor nodes based on the data from the embedded accelerometer and the inclinometer. Comparing the results from two sensor nodes deployed away and on the track respectively, the passing of the tunnel boring machine can be identified from unusual performances. Using this method, the ground settlement due to excavation can be measured and a real-time monitoring of ground subsidence can be realized.