Civil infrastructure failure is hard to predict, both in terms of occurrence and impact. This is due to combination of many factors, including highly variable environmental and operational conditions, complex construction and materials, and the sheer size of these structures. Often, the mitigation strategy is visual inspection and regular maintenance, which can be time-consuming and may not address root causes of failure. One potential solution to anticipating infrastructure failure and mitigating its consequences is the use of distributed sensors to monitor the physical state of a structure, an area of research known commonly as structural health monitoring, or SHM. This approach can be applied in a variety of contexts: safety during and after natural disasters, evaluation of building construction quality and life-cycle assessment for performance based design frameworks.
In one way or another, SHM methods always require a ``baseline,'' a set of physical features which describes the behavior of a healthy structure. Often, the baseline is defined in terms of modal parameters: natural frequencies, damping ratios, and mode shapes. Although changes in modal parameters are indicative of structural damage, they are also indicative of a slew of non-damage factors, such as signal-to-noise ratio, environmental conditions, and the characteristics of forces exciting the structure. In many cases, the degree of observed modal parameter changes due to non-damage factors can be much greater than that due to damage itself. This is especially true of low-frequency modal parameters. For example, the fundamental frequency of a building is more sensitive to global influences like temperature than local structural changes like a cracked column.
It has been proposed that extracting modal parameters at higher frequencies may be the key to improving the damage-sensitivity of SHM methods. However, for now, modal analysis of civil structures has been limited to low frequency ambient excitation and sparse sensor networks, due to practical limitations. Two key components for high-frequency modal analysis have yet to be studied: 1) Sufficient excitation at high frequencies and 2) high-resolution (high sensor density) measurements. The unifying goal of this work is to expand modal analysis in these two areas by applying novel instrumentation and experimental methods to two full-scale buildings, Goodwin Hall and Ernest Cockrell Jr. Hall. This enables realistic, practical insights into the limitations and benefits of the high-frequency SHM approach. Throughout, analyses are supported through the novel integration of uncertainty quantification techniques which so far has been under-utilized in the field.
This work is divided into three experimental areas, with approaches centering on the identification of modal parameters. The first area is the application of high spacial resolution sensor networks in combination to ambient vibration testing. The second is the implementation of a robust automation and monitoring strategy for complex dynamic structures. The third is the testing of a novel method for performing experimental modal analysis on buildings emph{in situ}. The combination of results from these experiments emphasizes key challenges in establishing reliable high-frequency, high-resolution modal parameter ``baselines'' for structural health monitoring (SHM) of civil infrastructure.
The first study presented in this work involved the identification of modal parameters from a five-story building, Goodwin Hall, using operational modal analysis (OMA) on ambient vibration data. The analysis began with a high spacial density network of 98 accelerometers, later expanding this number to 117. A second extensional study then used this data as reference to implement a novel automation method, enabling the identification of long-term patterns in the building's response behavior. Three dominant sources of ambient excitation were identified for Goodwin Hall: wind, human-induced loading, and consistent low-level vibrations from machinery, etc. It was observed that the amplitude of excitation, regardless of source, had significant effects on the estimated natural frequencies and damping ratios. Namely, increased excitation translated to lower natural frequencies and higher damping. In addition, the sources had different characteristics in terms of excitation direction and bandwidth, which contributed to significantly different results depending on the ambient excitation employed. This has significant implications for ambient-based methods that assume that all ambient vibrations are broadband random noise.
The third and final study demonstrated the viability of emph{in situ} seismic testing for controlled excitation of full-scale civil structures, also known as experimental modal analysis (EMA). The study was performed by exciting Ernest Cockrell Jr. Hall in Austin, Texas with both vertical and lateral ground waves from seismic shaker truck, T-Rex. The EMA results were compared to a standard operational modal analysis (OMA) procedure which relies on passive ambient vibrations. The study focused on a frequency bandwidth from 0 to 11 Hz, which was deemed high frequency for such a massive structure. In cases were coherence was good, the confidence comparable or better than OMA, with the added advantage that the EMA tests took only a fraction of the time. The ability to control excitation direction in EMA enabled the identification of new structural information that was not observed OMA. It is proposed that the combination of high spacial resolution instrumentation and emph{in situ} excitation have the potential to achieve reliable high-frequency characterization, which are not only more sensitive to local damage but also, in some cases, less sensitive to variations in the excitation conditions. / Ph. D. / Civil structures, like buildings and bridges, become weaker as they age, increasing their risk of collapse due to sever weather, earthquakes, and heavy traffic. Engineers regularly inspect civil structures to ensure they are in good shape, but it is difficult do a full assessment by eye since many defects can be hidden. Structural Health Monitoring, or SHM for short, is an approach that uses permanent vibration sensors to continuously inspect civil structures. Any activity, like blowing wind or moving traffic on bridge, produces small vibrations which can be analyzed to assess the “health” of the structure. This approach can detect some invisible defects, but there is still debate about whether it can detect them when they are small and early on in the life of a structure. If SHM can’t issue early warnings, then there is little incentive to spend large amounts of money on a sensor system.
To capture small defects, a sensor system needs a large number of sensors, hence the term high-resolution in the title. In addition, the structure being tested needs to vibrate rapidly (that is at high-frequencies) in order for the high-resolution information to be useful. So far, there have been no tests of this kind on civil structures, especially buildings. Instead, most sensor systems have contained a relatively low number of sensors tested with low-frequency vibrations.
This works fills in this gap by testing two different buildings with SHM sensor systems. The first experiment uses a very high number of sensors to analyze the vibrations of Goodwin Hall on the Virginia Tech campus. The vibrations in this building are produced by wind and people walking inside. The second experiment uses a standard number of sensors, but explores a new method of vibrating buildings. This method uses a truck with a large hydraulic piston to shake the ground near the E. Cockrell Jr. building (University of Austin-Texas), essentially creating a tiny earthquake. The experiments show that both testing techniques provide more useful information than standard ones alone. For the first experiment, using more sensors meant the analysis could better distinguish the structural characteristics of the building. For the second, the artificial “earthquake” enabled the measurement of high-frequency vibrations, something which was not possible by relying on wind or people to vibrate the building.
Although these new approaches are not used to inspect for damage, they have laid the foundation for improving the early-warning capabilities of SHM systems. This could mean that buildings and other structures can be repaired sooner, remain in operation longer, and cost the owners less money in the end!
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/84477 |
| Date | 02 August 2018 |
| Creators | Sarlo, Rodrigo |
| Contributors | Mechanical Engineering, Tarazaga, Pablo Alberto, Wicks, Alfred L., Eatherton, Matthew R., Ventura, Carlos E., West, Robert L. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf, application/vnd.openxmlformats-officedocument.wordprocessingml.document |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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