In this paper, we will summarize our efforts on exploring guided acoustic waves generated by MEMS ultrasonic
transducers enabling a non-destructive, ultra-low powered, wireless SHM system. State-of-the-art SHM systems employ
bulk piezoelectric transducers. However, they are not environmentally benign (contain lead), not cost feasible for
monitoring every bridge in the U.S., require significant power for operation, lack integration capability for wireless
interrogation, need precise matching layers, and have only 25-50 percent fractional bandwidth, limiting the detection
resolution. To alleviate most of these shortcomings, a low impedance MEMS transducer, called a capacitive
micromachined ultrasonic transducer (CMUT), is explored.
KEYWORDS: Autoregressive models, Data modeling, Mahalanobis distance, Structural health monitoring, Pattern recognition, Detection and tracking algorithms, Statistical analysis, Time series analysis, Data analysis, Aerospace engineering
Identification of damage in a structure, or structural change in general, has been a challenging problem for the
researchers in Structural Health Monitoring (SHM) area. Over the last a few decades, a number of experimental and
analytical techniques have been developed and used to solve such problem. It has been has been recently accepted in the
literature that the process of damage identification problem is one where statistical pattern recognition techniques can be
of use because of the inherent uncertainties of the problem. Time series analysis is one of the methods, which is
implemented in statistical pattern recognition applications to SHM. In previous studies, Auto-Regressive (AR) models
are highly utilized for this purpose. In this study, AR model coefficients are used with different outlier detection and
clustering algorithms to detect the change in the boundary conditions of a steel beam. A number of different boundary
conditions are realized by using different types and amounts of elastomeric pads. The advantages and the shortcomings
of the methodology are discussed in detail based on the experimental results in terms of the ability of it to detect the
structural changes and localize them.
The purpose of this paper is to present an overview of experimental structural dynamics as a unique technology for global health monitoring of large structures. Assessment of damage and objective condition evaluation of existing civil infrastructure systems (CIS) are important needs for making decisions during regular operation as well as before and after disasters. Objective condition assessment is also a fundamental knowledge need for successful health monitoring of
CIS. In this paper, the writers discuss promises as well as the challenges for dynamic measurements, and the use of modal flexibility matrices for condition assessment when dynamic methods are applied on large structures. They present snapshots from their past and current studies where dynamic tests were implemented on medium and long span bridges
KEYWORDS: Finite element methods, Bridges, Data acquisition, Composites, Reliability, Data modeling, Mathematical modeling, Data processing, Error analysis, Manufacturing
In this paper a structural identification (St-Id) case study on a laboratory physical model is presented. The main objective is to understand the reliability of ambient monitoring as the principal global experimentation tool for St-Id and to address the issues related to the projection of the laboratory study to a bridge structure. Linear deterministic FE modeling, controlled static load tests, impact tests and ambient vibration tests are utilized as St-Id tools to supplement each other in the study. The results showed that even under controlled laboratory conditions, uncertainties in the St-Id process cannot be completely avoided and govern the reliability of an St-Id study. Issues regarding the successful application of ambient vibration testing on a real-life bridge structure based on laboratory model results are addressed.
Significance of effectively managing civil infrastructure systems (CIS) throughout CIS life-cycles, and especially during and after natural or man-made disasters is well recognized. Disaster mitigation includes preparedness for hazards to avoid casualties and human suffering, as well as to ensure that critical CIS components can become operational within a short amount of time following a disaster. It follows that mitigating risk due to disasters and CIS managementare intersecting and interacting societal concerns. A coordinated, multi-disciplinary approach that integrates field, theoretical and laboratory research is necessary for innovating both hazard mitigation and infrastructure management. Health monitoring (HM) of CIS is an emerging paradigm for effective management, including emergency response and recovery management. Challenges and opportunities in health monitoring enabled by recent advances in information technology are discussed in this paper. An example of HM research on an actual CIS test-bed is presented.
KEYWORDS: Bridges, Finite element methods, Statistical analysis, Data modeling, Optical inspection, Inspection, Databases, Nondestructive evaluation, Information technology, Geographic information systems
The importance of rational decision-making for optimum resource distribution of civil infrastructure systems management is well recognized. Bridges, serving as node points of the highway transportation system, are critical components of the nation's infrastructure. As the nation's bridge population is aging, management decisions must be based on an objective, complete, accurate and compatible information for maximum reliable bridge lifecycle. For bridges sharing common materials, similar geometric design attributes and behavior mechanisms, fleet-strategies for health monitoring would offer significant advantages. Improvements from fleet health monitoring would lead to objective engineering knowledge for optimal decision making. This paper provides an overview of fleet health monitoring concept, then summarizes an on-going research on re- qualification of reinforced concrete T-beam bridge population in Pennsylvania.
Structural identification (St-Id) of constructed systems is of interest to researchers as well as civil infrastructure systems owners and operators. St-Id offers an objective, quantitative evaluation of constructed systems through effective and integrated utilization of state-of-the-art experimental and analytical technologies. During the past five years two test beds were created at the University of Cincinnati and Drexel University for the exploration of analytical and experimental barriers obstructing successful St-Id applications. The two physical models are plane-grid structures with different controlled mechanisms of uncertainty. The objective of this paper is to present the St-Id studies to the two physical models. The principal mechanisms of uncertainty that governed the global structure behavior of the first physical model were nonlinear visco- elastic boundaries. The second model incorporated a fiber- reinforced polymer composite deck and its connection details to the grid. The impact of these different mechanisms of uncertainty on the success of St-Id will be addressed.
KEYWORDS: 3D modeling, Bridges, Computer aided design, Solid modeling, Analytical research, Calibration, Data modeling, Data acquisition, Finite element methods, Visual process modeling
The Commodore Barry Bridge is a major long-span bridge across the Delaware River connecting the cities of Bridgeport, New Jersey and Chester, Pennsylvania. A Structural Identification (St-Id) study of Commodore Barry Bridge is presented. The objective of this structural identification approach is to characterize the as-is structural condition and the loading environment of the bridge through experimental information and analytical modeling. The attributes that make long-span bridges different for utilization of experimental and analytical applications as compared to short-span bridges are presented. Some of the experimental, analytical and information tools which are utilized for this research are discussed. The details of constructing a preliminary analytical model after conceptualization of the structural characteristics are presented. Development of the 3D analytical model, and the model characteristics such as elements used, boundary and continuity representations are summarized. The experimental techniques that are necessary for the structural identification of a long span bridge are defined and application examples are provided from the Commodore Barry Bridge. Experiences gained during the applications of different forms of dynamic tests, instrumented monitoring and controlled static and crawl speed load tests are presented with example experimental data. Correlation of experimental results and analytical simulations are presented. Immediate and possible future uses of information generated are summarized.
The objective of this paper is to present and discuss the most critical issues the writers have identified as needing resolution in order to implement meaningful and beneficial applications of health-monitoring. The challenges in the integration of intelligent transportation and structural systems concepts within an optimum integrated asset management framework will be overviewed. Examples from ongoing research on the health-monitoring of short-span bridge families and long-span bridges will be offered to illustrate the issues.
On-line, continuous monitoring technologies of a rigorous and objective nature are sought to quantitatively identify and evaluate the condition or health of highway structures over their useful lifetime. A global bridge evaluation methodology is under development based upon the structural identification concept, employing modal testing, truckload testing, and instrumented monitoring as its principal experimental tools. Test results are transformed to either modal flexibility or the unit influence line, which have been demonstrated to be conceptual, quantitative, comprehensive, and damage-sensitive signatures. Four test sites were tested, monitored, and studied in order to classify their similar bride-type-specific behavior mechanisms and to validate the performance of the implemented methodology. Practical, type-specific procedures for instrumented monitoring and nondestructive evaluation can then be developed for the whole group or type of highway bridges.
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