Electrical conductivity (or resistivity) of cementitious materials is considered to be a fundamental property and is commonly measured using nondestructive and noninvasive testing techniques. Therefore, electrical measurements are gaining popularity in both research and field applications for structural health monitoring and material characterization of civil engineering infrastructure systems. Based on the results of measurements, the engineer can schedule maintenance more accurately and give an early warning of possible structural failure. Recently, health monitoring systems are capable of significantly increasing the cost efficiency of maintenance and repair by helping engineers improve the safety and maintainability of structures through early damage detection. The research team at the University of Texas at Austin developed a low-cost, passive, wireless conductivity sensor system. Sensors are wirelessly interrogated using external reader during inspection over the service life of the structure to monitor the conductivity variations within concrete. The focus of this work is to assess the condition of cementitious materials by measuring electrical conductivity using passive wireless sensors. By analyzing the measured conductivity data, the condition of the cementitious material, such as extent of hydration, setting and hardening times, and transport phenomena, can be assessed. This document also provides comprehensive information on the design, fabrication, interrogation, and response of conductivity sensor platforms. / text

Due to their structural efficiency and architectural elegance, concrete arches have long been used in bridge applications. However, the construction of concrete arches requires significant temporary supporting structures, which prevent their widespread use in modern bridges. A relatively new form of arch bridges is the network arch, in which a dense arrangement of inclined hangers is used. Network arches are subjected to considerably smaller bending moments and deflections than traditional arches and are therefore suitable for modern, accelerated construction methods in which the arches are fabricated off-site and then transported to the bridge location. However, service-level stresses, which play a critical role in the performance of the structure, are relatively unknown for concrete network arches and have not been sufficiently investigated in the previous research on concrete arches. The primary objective of this dissertation is to improve the understanding of short-term and time-dependent stresses in concrete arches, and more specifically, concrete network arches. The research presented herein includes extensive field monitoring of the West 7th Street Bridge in Fort Worth, Texas, which is the first precast network arch bridge and probably the first concrete network arch bridge in the world. The bridge consists of twelve identically designed concrete network arches that were precast and post-tensioned before they were transported to the bridge site and erected. A series of vibrating wire gages were embedded in the arches and were monitored throughout the construction and for a few months after the bridge was opened to traffic. The obtained data were processed, and structural response parameters were evaluated to support the safe construction of the innovative arches, identify their short-term and time-dependent structural behavior, and verify the modeling assumptions. The variability of stresses among the arches was also used to assess the reliability of stress calculations. The results of this study provide valuable insight into the elastic, thermal, and time-dependent behavior of concrete arches in general and concrete network arches in particular. The knowledge gained in this investigation also has broader applications towards understanding the behavior of indeterminate prestressed concrete structures that are subjected to variable boundary conditions and thermal and time-dependent effects.

Detection and monitoring of the damage created by the corrosion of the steel reinforcement in concrete structures is a challenging and multidisciplinary problem. Economical monitoring strategy that is long-term and nondestructive requires low-cost, battery-free, wireless sensors. Our Electronic Structural Surveillance (ESS) platform uses battery-free passive resonant circuit (tag) as a sensor. The tag is magnetically coupled to an external reader coil. It is interrogated/read remotely in a non-contact (wireless) manner and the state of the sensor is determined from a swept frequency impedance measurement. When paired with the correct sensing element (transducer), the tag can be used for a variety of sensing applications for example, chemical & biochemical sensors. A circuit model of the reader and tag for such a universal battery-free wireless sensor platform is developed. The interaction between design and detection limit is examined. The dependence of the measured signal strength and read range on the various reader and tag circuit parameters is analyzed. Since the values of the circuit of the coils are dependent on their geometries, the effect of specific coil geometry is evaluated and design recommendations are made. / text

The early detection of damage of in-service structural or mechanical systems is of vital importance. With early detection, the damage may be repaired before the integrity of the system is jeopardized, avoiding possible monetary losses, environmental impacts, injury and death. With this goal in mind, many structural health monitoring techniques have been developed which use a combination of sensors and algorithms to collect, process and interpret data to detect damage in a structure. This thesis presents work completed in support of the experimental validation of a novel structural health monitoring technique developed with the aim of providing improved qualitative results compared to those methods currently available.

Structural Health Monitoring (SHM) is widely used to monitor the short and long-term behavior of intelligent structures. This monitoring can help prolong the useful service lives and identify deficiencies before possible damage of such structures. The sensing systems that are usually deployed are intended to faithfully relay readings that reflect the true conditions of these structures. Unfortunately, this is seldom the case due to the presence of errors in the collected data. The electrical strain gauges used in SHM environments for instrumentation purposes are susceptible to numerous sources of error. Apparent strain is known to be the most serious of all such errors. However or whichever way temperature variations of the gauge’s environment occurs, apparent strain is introduced. This work focuses on modeling apparent strain in an SHM environment using National Instruments’ (NI) hard and software. The results of this work are applicable for thermal compensation in current test programs.

This dissertation develops a robust, data-driven localization methodology based on the integration of matched field processing with compressed sensing ℓ1 recovery techniques and scale transform signal processing. The localization methodology is applied to an ultrasonic guided wave structural health monitoring system for detecting, locating, and imaging damage in civil infrastructures. In these systems, the channels are characterized by complex, multi-modal, and frequency dispersive wave propagation, which severely distort propagating signals. Acquiring the characteristics of these propagation mediums from data represents a difficult inverse problem for which, in general, no readily available solution exists. In this dissertation, we build data-driven models of these complex mediums by integrating experimental guided wave measurements with theoretical wave propagation models and ℓ1 sparse recovery methods from compressed sensing. The data-driven models are combined with matched field processing, a localization framework extensively studied for underwater acoustics, to localize targets in complex, guided wave environments. The data-driven matched field processing methodology is then refined, through the use of the scale transform, to achieve robustness to environmental variations that distort guided waves. Data-driven matched field processing is experimentally applied to an ultrasound structural health monitoring system to detect and locate damage in aluminum plate structures.

Structural Health Monitoring (SHM) is widely used to monitor the short and long-term behavior of intelligent structures. This monitoring can help prolong the useful service lives and identify deficiencies before possible damage of such structures. The sensing systems that are usually deployed are intended to faithfully relay readings that reflect the true conditions of these structures. Unfortunately, this is seldom the case due to the presence of errors in the collected data. The electrical strain gauges used in SHM environments for instrumentation purposes are susceptible to numerous sources of error. Apparent strain is known to be the most serious of all such errors. However or whichever way temperature variations of the gauge’s environment occurs, apparent strain is introduced. This work focuses on modeling apparent strain in an SHM environment using National Instruments’ (NI) hard and software. The results of this work are applicable for thermal compensation in current test programs.

Advanced composite materials are becoming increasingly more valuable in a plethora of engineering applications due to properties such as tailorability, low specific strength and stiffness and resistance to fatigue and corrosion. Compared to more traditional metallic and ceramic materials, advanced composites such as carbon, aramid or glass reinforced plastic are relatively new and still require research to optimize their capabilities. Three areas that composites stand to benefit from improvement are processing, damage detection and life prediction. Fiber optic sensors and piezoelectric transducers show great potential for advances in these areas. This dissertation presents the research performed on improving the efficiency of advanced composite materials through the use of embedded fiber optic sensors and surface mounted piezoelectric transducers. Embedded fiber optic sensors are used to detect the presence of resin during the injection stage of resin transfer molding, monitor the degree of cure and predict the remaining useful life while in service. A sophisticated resin transfer molding apparatus was developed with the ability of embedding fiber optics into the composite and a glass viewing window so that resin flow sensors could be verified visually. A novel technique for embedding optical fiber into both 2- and 3-D structures was developed. A theoretical model to predict the remaining useful life was developed and a systematic test program was conducted to verify this model. A network of piezoelectric transducers was bonded to a composite panel in order to develop a structural health monitoring algorithm capable of detecting and locating damage in a composite structure. A network configuration was introduced that allows for a modular expansion of the system to accommodate larger structures and an algorithm based on damage progression history was developed to implement the network. The details and results of this research are contained in four manuscripts that are included in Appendices A-D while the body of the dissertation provides background information and a summary of the results. / Graduate

The research effort in this thesis is devoted to develop techniques to accurately and rapidly identify the location, orientation, and magnitude of the defects by using structural health monitoring concepts that use Laser Doppler Vibrometer as a non-contact sensor with multi-point sensing capability. The first research area addresses the formulation and validation of an innovative Damage Measure that is based on the ratios of the strain energy distributions of the damaged and undamaged structure. The innovations include use of a single set of actuator/sensor pair to excite and detect the responses of a structure for low frequency vibrations as well as guided wave propagation studies. A second new capability is the estimation of the Damage Measure without requiring any knowledge of the undamaged baseline structure. This method is made possible because of the development of these new technologies: Spatial Decimation and Wavenumber/Frequency filtering. The third contribution is to develop analytical models for the structural dynamics of damaged structure and seek solutions that use perturbation methods to detect damage in a plate structure. The fourth contribution is the development of a comprehensive damage detection technique over a wide frequency dynamic range. The fifth topic of research involves automation in Structural Health Monitoring based on the comprehensive Damage Measure formulation. Under the control of software the Scanning Laser Doppler Vibrometer is used to acquire the low frequency vibration mode data for a coarse identification of all the suspect regions of damage using a threshold criterion on the Damage Measure. Each suspect region of damage is further investigated using the high frequency elastic wave propagation to clearly identify the location, orientation, and extent of the damage. The computer control of the Laser Doppler Vibrometer and a quantitative assessment of the damage provide the enabling technologies for the automation proof of concept. Finally the developed techniques of damage detection are successfully demonstrated on practical structures such as a turbine blade in the laboratory and an F-15 vertical tail in field maintenance conditions

Thesis (M.S.)--University of Texas at El Paso, 2009. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.