Use of Microwaves for Damage Detection of Fiber Reinforced Polymer-Wrapped Concrete Structures

Jacketing technology using fiber reinforced polymer (FRP) composites is being applied for seismic retrofit and rehabilitation of reinforced concrete (RC) columns designed and constructed under older specifications. In this study, the authors develop an electromagnetic (EM) imaging technology for detecting such damage as voids and debonding between the jacket and the column, which may significantly weaken the structural performance of the column otherwise attainable by jacketing. This technology is based on the reflection analysis of a continuous EM wave sent toward and reflected from layered FRP–adhesive-concrete medium: Voids and debonding areas will generate air gaps which produce additional reflections of the EM wave. In this study, dielectric properties of various materials involved in the FRP-jacketed RC column were first measured using a plane-wave reflectometer. The measured properties were then used for a computer simulation of the proposed EM imaging technology. The simulation demonstrated the difficulty in detecting damage by using plane waves, as the reflection contribution from the voids and debonding is very small compared to that from the jacketed column. In order to alleviate this difficulty, dielectric lenses were designed and fabricated, focusing the EM wave on the bonding interface. Finally, three concrete columns were constructed and wrapped with glass–FRP jackets with various voids and debonding conditions artificially introduced in the bonding interface. Using the proposed EM imaging technology involving the especially designed and properly installed lenses, these voids and debonding areas were successfully detected. This technology can be used to assess the jacket bonding quality during the initial jacket installation stage and to detect debonding between the column and the jacket caused by earthquake and other destructive loads

Determination of Intrinsic Ferroelectric Polarization in Orthorhombic Manganites with E-type Spin Order

By directly measuring electrical hysteresis loops using the Positive-Up Negative-Down (PUND) method, we accurately determined the remanent ferroelectric polarization Pr of orthorhombic RMnO3 (R = Ho, Tm, Yb, and Lu) compounds below their E-type spin ordering temperatures. We found that LuMnO3 has the largest Pr of 0.17 uC/cm^2 at 6 K in the series, indicating that its single-crystal form can produce a Pr of at least 0.6 \muuC/cm^2 at 0 K. Furthermore, at a fixed temperature, Pr decreases systematically with increasing rare earth ion radius from R = Lu to Ho, exhibiting a strong correlation with the variations in the in-plane Mn-O-Mn bond angle and Mn-O distances. Our experimental results suggest that the contribution of the Mn t2g orbitals dominates the ferroelectric polarization.Comment: 16 pages, 4 figure

Microwave Subsurface Imaging Technology for Damage Detection

This paper presents a technology for detecting invisible damage inside concrete, which is based on reconstruction of dielectric profile (image) of the concrete illuminated with microwaves sent from and received by antenna arrays controlled by specialized software. The imaging system developed in this study consists of an 8X8 transmitting and an 8X8 receiving arrays, an innovative numerical bifocusing operator for improving image resolution, and imaging software for reconstructing a two-dimensional image from the scattered field. The effectiveness of the of the developed technology in detecting steel and voids inside concrete has been demonstrated through numerical simulation and experiments

Baseline Models for Bridge Performance Monitoring

A baseline model is essential for long-term structural performance monitoring and evaluation. This study represents the first effort in applying a neural network-based system identification technique to establish and update a baseline finite element model of an instrumented highway bridge based on the measurement of its traffic-induced vibrations. The neural network approach is particularly effective in dealing with measurement of a large-scale structure by a limited number of sensors. In this study, sensor systems were installed on two highway bridges and extensive vibration data were collected, based on which modal parameters including natural frequencies and mode shapes of the bridges were extracted using the frequency domain decomposition method as well as the conventional peak picking method. Then an innovative neural network is designed with the input being the modal parameters and the output being the structural parameters of a three-dimensional finite element model of the bridge such as the mass and stiffness elements. After extensively training and testing through finite element analysis, the neural network became capable to identify, with a high level of accuracy, the structural parameter values based on the measured modal parameters, and thus the finite element model of the bridge was successfully updated to a baseline. The neural network developed in this study can be used for future baseline updates as the bridge being monitored periodically over its lifetime

Microwave reflection tomographic array for damage detection of civil structures

Microwave tomographic imaging technology using a bifocusing operator has been developed in order to detect the internal voids/objects inside concrete structures. The imaging system consists of several cylindrical or planar array antennas for transmitting and receiving signals, and a numerical focusing operator is applied to the external signals both in transmitting and in receiving fields. An imaging algorithm using numerical focusing operator was developed, which allows the recovery of a two-dimensional object from its scattered field. Numerical simulation demonstrated that a subsurface image can be successfully reconstructed by using the proposed tomographic imaging technology. For the experimental verification, a prototype planar antenna array was fabricated and tested on a concrete specimen.Peer Reviewe