Advances in sensor technology and computer science in the last three decades have boosted the importance of system identification and vibration-based structural health monitoring (SHM) in civil infrastructure safety and integrity assessment. On the other hand, practical and financial issues in system instrumentation, maintenance, and operation have remained as fundamental problems obstructing the widespread use of SHM applications. For this reason, to reduce system costs and improve practicality as well as sustainability, researchers have been working on emerging methods such as wireless, distributed, mobile, remote, smart, multisensory, and heterogeneous sensing systems. Smartphones with built-in batteries, processor units, and a variety of sensors, have stood as a promising hardware and software environment that can be used as SHM components. Communication capabilities with the web, enable them to compose a smart and participatory sensor network of outnumbered individuals. Besides, crowdsourcing power offered by citizens, sets a decentralized and self-governing SHM framework which can even be pertained by very limited equipment and labor resources. Yet, citizen engagement in an SHM framework brings numerous challenges as well as opportunities. In a citizen-induced SHM scenario, the system administrators have limited or no control over the sensor instrumentation and the operation schedule, and the acquired data is subjected change depending on the measurement conditions. The citizen-induced errors can stem from spatial, temporal, and directional uncertainties since the sensor configuration relies on smartphone users’ decisions and actions. Moreover, the sensor-structure coupling may be unavailable where the smartphone is carried by the user, and as a consequence, the vibration features measured by smartphones can be modified due to the human biomechanical system. In addition, in contrast with the conventional high fidelity sensors, smartphone sensors are of limited quality and are subjected to high noise levels. This dissertation utilizes multisensory smartphone features to solve citizen-induced uncertainties and develops a smartphone-based SHM methodology which enables a cyber-physical system through mobile crowdsourcing. Using smartphone computational and communicational power, combined with a variety of embedded sensors such as accelerometer, gyroscope, magnetometer and camera, spatiotemporal and biomechanical citizen-induced uncertainties can be eliminated from the crowdsourced smartphone data, and eventually, structural vibrations collected from numerous buildings and bridges can be collected on a single cloud server. Therefore, unlike the conventional platforms designed and implemented for a particular structure, citizen-engaged and smartphone-based SHM can serve as intelligent, scalable, fully autonomous, cost-free, and durable cyber-physical systems drastically changing the forthcoming trends in civil infrastructure monitoring. In this dissertation, iOS is used as the application development platform to produce a smartphone-based SHM prototype, namely Citizen Sensors for SHM. In addition, a web-based software is developed and cloud services are implemented to connect individual smartphones to an administrator base and automate data submission and processing procedure accordingly. Finally, solutions to citizen-induced problems are provided through numerous laboratory and field test applications to prove the feasibility of smartphone-based SHM with real life examples. Through collaborative use of the software, principles and methodologies presented in this dissertation, smartphones can be the core component of futuristic smart, resilient, and sustainable city and infrastructure systems. And this study lays down an innovative and integrated foundation empowering citizens to achieve these goals.

Computer vision sensing techniques enable easy-to-install and remote non-contact monitoring of structures and have great potentials in field applications. This study will develop/implement novel computer vision techniques for two sensing systems for monitoring different aspects of infrastructures in challenging field conditions. The dissertation is therefore composed of two parts: robust measurement of global multi-point structural displacements, and accurate and robust monitoring of local surface displacements/strains. Computer vision based displacement measurement has become popular in the recent decade. The first part presents InnoVision, a vision sensing system developed to address a number of challenging problems associated with applying vision sensors to the measurement of multi-point structural displacement in field conditions that are rarely comprehensively studied in the literature. The challenging problems include tracking low-contrast natural targets on the structural surface, insufficient resolution for long distance measurement, inevitable camera vibration, and image distortion due to heat haze in hot weather. Several techniques are developed in InnoVision to tackle these challenges. Laboratory and field tests are conducted to evaluate the performance of these techniques. In the second part, another vision sensing system SurfaceVision is developed for accurate and robust monitoring two-dimensional (2D) structural surface displacements/strains. Important structures, such as nuclear power plants, need the continuous inspection of surface conditions. As an alternative to the human inspection, conventional digital-image-correlation (DIC) based methods have been applied to surfaces painted with speckle patterns in a controlled environment. However, it is highly challenging for DIC methods to accurately measure displacement on natural concrete surfaces in outdoor conditions with changing illumination and weather conditions. Additionally, common surface displacement measurement is based on segmenting the surface image into small subsets and tracking each subset individually through template matching, the surface displacement thus obtained has obvious discontinuity and low spatial resolution. Therefore, for applicability in the outdoor environment, SurfaceVision is proposed for accurate and robust monitoring of surface displacements/strains. Advanced computer vision techniques are developed/implemented to enable surface displacement measurement with high continuity, spatial resolution, accuracy, and robustness. An intuitive strain calculation method is also developed for converting surface displacements into surface strains. A numerical simulation is formulated based on four-point bending tests to validate the accuracy and robustness of SurfaceVision in surface displacements. Four-point bending experiments using reinforced concrete specimens are conducted to demonstrate the performance of SurfaceVision under different cases of optical noises and its effectiveness in predicting crack formations.

The western and northern parts of South Florida have shallow layers of organic and plastic soils under existing roads. These roads often exhibit large amount of cracking and distortion in a short period of time. Traditional repairs are often not practical due to high costs and extended construction time. In an effort to develop rehabilitation strategies that could be strictly applied to the surface layer, a pilot test site was selected along the alignment of SR 15/US 98 in northwest Palm Beach County, where severe pavement distresses were observed due to the presence of thick organic layers. PaveTrac MT-1, GlasGrid 8501, PetroGrid 4582, and ARMI were used as promising asphalt reinforcing products in 24 experimental pavement sections, including 8 control sections without any reinforcement. A comprehensive field testing and monitoring program involving FWD, rut and ride quality measurements was conducted at the preconstruction, 6-month post-construction, and 18-month post-construction stages. Due to large variability in the sub-surface conditions, a statistics-based data analysis protocol was developed for performance evaluation and relative comparisons of the test sections and, in turn, reinforcing products. Post construction data from both 6 months and 18 months demonstrated that stiffness of reinforced sections were significantly higher than the control sections. Procedures were developed to identify and statistically quantify the benefits derived from the reinforcements only, so that the relative performance of various products could be monitored over time. Based on the field testing data available to date, a framework was developed in this study for the prediction of pavement life, which is essential for conducting a detailed Life Cycle Analysis / by Alex Lima-Arie. / Thesis (M.S.C.S.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.

In an attempt to achieve more efficient designs, the technological frontier is pushed further and further. Every year science probes for a better understanding of natural phenomena, discovering new and improved methods to perform the same task more efficiently and with better results. One of the new technologies is the nonlinear analysis of structural systems using inelastic post-buckling member performance. Inelastic post-buckling member performance is defined as the constitutive relationship between axial load and displacement after the ultimate member capacity has been exceeded. A nonlinear analysis is able to predict the failure behavior of a structural system under ultimate loads more accurately than the traditionally used linear elastic analysis. Consequently, designs can be improved and become more efficient, which reduces the realization cost of a project. An improved nonlinear analysis solution algorithm has been developed, that allows the analyst to perform a nonlinear analysis using post-buckling member performances faster than previously possible. Furthermore, the original post-buckling member performance database was expanded using results obtained from physical member compression tests. Based on the experimental results, new post-buckling member performance model curves were developed to be used together with the improved nonlinear solution algorithm. In addition, a program was developed that allows the analyst to perform a valid nonlinear analysis using a finite element program (LIMIT). The program combines a numerical pre-processor, and input and output data evaluation modules based on human expertise together with the LIMIT analysis package. Extensive on-line help facilities together with graphical pre- and post-processors were also integrated into the program. The resulting analysis package essentially combines all of the necessary components required to perform a nonlinear analysis using post-buckling member performances into one complete analysis package.

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This thesis investigates the behaviour of hollow and concrete filled steel columns fabricated from thin steel plates. The columns are investigated under axial, uniaxial and biaxial loading. The currently available international standards for composite structures are limited to the design of concrete filled steel columns with compact sections and yield stress of steel up to 460 N/mm2. This thesis consists of both experimental and analytical studies and design recommendations for future use. Three comprehensive series of experimental tests are conducted on hollow and concrete filled steel columns. The principal parameters that have been considered in the test programmes are the slenderness of the component plates, the yield stress of the steel and the loading conditions. In the first test series, three slender hollow steel columns and three slender composite columns are tested under uniaxial loading. The steel utilised is mild steel. High strength steel is utilised in the second test programme. In this test series four stub columns, eight short columns and eight slender columns are tested, each set consists of four hollow and four composite columns. Short columns are tested under axial loading to investigate the confinement effect provided by the steel casing. Slender columns are tested under uniaxial loading to investigate the coupled instability of local and global buckling. The third test programme is quite novel and considers the behaviour of hollow and concrete filled steel columns fabricated with high strength structural steel plate and subjected to biaxial bending. In this test eight short columns and ten slender columns each of them consisting of hollow and composite columns are investigated under biaxial loading. Analytical models are developed herein to elucidate the behaviour of the hollow and composite columns considering cross section slenderness, yield stress and loading conditions. An iterative model considering the coupled global and local buckling in the elastic and plastic range incorporating material nonlinearities is developed to investigate the behaviour of slender columns fabricated from mild steel. An improved deformation control model is developed to investigate the behaviour of slender high strength steel columns considering the confinement effect and local and post-local buckling in the elastic and plastic range. Then a numerical model for biaxial bending is developed to study the behaviour of short and slender concrete filled high strength steel columns under biaxial loading incorporating interaction buckling considering material and geometric nonlinearities. The scope of the thesis presents a wide range of experimental and theoretical studies of an extremely novel nature. It demonstrates the benefit of confinement and the consideration of local and post-local buckling in the elastic and plastic range. It is hoped that this research will contribute to the area of composite steel-concrete structural applications.

Modern civil structures as well as loads on them are still too complex to be accurately modeled or simulated. Therefore, structural failures and structural defects are NOT uncommon! More and more full-scale structural monitoring systems have been deployed in order to monitor how structures behave under various loading conditions. This research focuses on how to maximise benefits from such full-scale measurements by employing advanced digital signal processing techniques. This study is based on accelerometer and GPS data collected on three very different structures, namely, the steel tower in Tokyo, the long and slender suspension bridge in Hong Kong, and the tall office tower in Sydney, under a range of loading conditions, i.e., typhoon, earthquake, heavy traffic, and small scale wind. Systematic analysis of accelerometer and GPS data has demonstrated that the two sensors complement each other in monitoring the static, quasi-static and dynamic movements of the structures. It has also been confirmed that the Finite Element Model could under-estimate the natural frequencies of structures by more than 40% in some case. The effectiveness of using wavelet to de-noise GPS measurement has been demonstrated. The weakness and strengths of accelerometer and GPS have been identified and framework has been developed on how to integrate the two as well as how to optimize the integration. The three-dimensional spectral analysis framework has been developed which can track the temporal evolution of all the frequency components and effectively represents the result in the 3D spectrogram of frequency, time and magnitude. The dominant frequency can also be tracked on the 3D mesh to vividly illustrate the damping signature of the structure. The frequency domain coherent analysis based on this 3D analysis framework can further enhance the detection of common signals between sensors. The developed framework can significantly improve the visualized performance of the integrated system without increasing hardware costs. Indoor experiments have shown the excellent characteristics of the optical fibre Bragg gratings (FBGs) for deformation monitoring. Innovative and low-cost approach has been developed to measure the shift of FBG???s central wavelength. Furthermore, a schematic design has been completed to multiplex FBGs in order to enable distributed monitoring. In collaboration with the University of Sydney, the first Australian full-scale structural monitoring system of GPS and accelerometer has been deployed on the Latitude Tower in Sydney to support current and future research.