Structural health monitoring of bridges for improving transportation security

Structural health monitoring (SHM) is a promising technology for determining the condition of significant transportation structures objectively for efficient management and preservation of transportation assets. In addition to identifying, locating, and quantifying damage and deterioration due to effects of operation, aging, and natural hazards, the need for taking terrorism-related hazards into account has become evident after 9/11 terrorist attacks. Key transportation facilities like major bridges were identified by Department of Homeland Security (DHS) as possible terrorist targets since their loss or even temporary deficiency could lead to major impacts on economy and mobility. Several governmental, local, and private organizations have been working on identifying possible modes of threats, determining and sorting vulnerable structures, and establishing ways to prevent, detect and respond to such attacks. Authorities are also investigating ways to integrate current and future bridge management systems with security surveillance systems. Highway bridges are key links of the transportation system. This paper reviews security measures for bridges and discuss possible integration of structural health and security monitoring for improving security and safety of bridges and emergency management after a natural or man-made disaster

Integration of BrIM and BMS to support bridge life-cycle management

The implementation of Bridge Management Systems (BMS) dates back to the 1970s and its adoption is nowadays generalized worldwide. Initially, they were used only as a database but, in the last decades, BMS potential is being highlighted. Tools to perform data analysis, integrating performance prediction models, have been added to the most advanced BMS. These are essential to support bridge managers in scheduling their maintenance interventions thus assuring their functionality conforms to the predefined expectations. Most of the existing BMS are currently software tools able to integrate a set of stakeholders involved during the bridge management. Hence, the adaptation of BMS to a digital environment must consider that aspect. In this regard, choosing an information exchange format that allows taking BMS into a digital context yet maintaining the interoperability between different stakeholders and their tools of preference is mandatory. In the context of construction’s digitalization, Building Information Modelling (BIM) is the main method being adopted. However, BIM was initially conceived for buildings, thus adaptation efforts are ongoing to also include other types of constructions, namely, civil infrastructures to which the bridges category belongs. This led to the appearance of the Bridge Information Modelling (BrIM) concept, which represents for bridges what BIM represents for buildings. The most widely used format in the BIM context for interoperability purposes is IFC. IFC is an open format that allows software vendor-independent data exchange. In this context, this paper presents an assessment of the existing knowledge about the applicability of the IFC for modelling bridge data. A review is made to verify the feasibility of using the current IFC version to describe the information contained in BMS. Main limitations are identified, and opportunities discussed, namely how the current IFC schema can be adapted to face the missing entities

Structural health monitoring of in-service tunnels

This work presents an overview of some of the most promising technologies for the structural health monitoring (SHM) of in-service tunnels. The common goal of damage or unusual behaviour detection is best pursued by an integrated approach based on the concurrent deployment of multiple technologies. Typically, traditional SHM systems are installed in problematic or special areas of the tunnels, giving information on conditions and helping manage maintenance. However, these methodologies often have the drawbacks of forcing the interruption of traffic for SHM system installation and monitoring only selected portions. Alternative solutions that would make it possible to keep the tunnel in normal operation and/or to analyse the entire infrastructure development through successive and continuous scanning stages, would be beneficial. In this paper, the authors will briefly review some traditional monitoring technologies for tunnels. Furthermore, the work is aimed at identifying alternative solutions, limiting or avoiding traffic interruptions

Editorial. The crux in bridge and transport network resilience - advancements and future-proof solutions

Bridges and critical transport infrastructure (CTI) are primary infrastructure assets and systems that underpin human mobility and activities. Loss of the functionality of bridges has consequences on the entire transport network, which is also interconnected with other networks, therefore cascading events are expected in the entire system of systems, leading to significant economic losses, business, and societal disruption. Recent natural disasters revealed the vulnerabilities of bridges and CTI to diverse hazards (e.g. floods, blasts, earthquakes), some of which are exacerbated due to climate change. Therefore, the assessment of bridge and network vulnerabilities by quantifying their capacity and functionality loss and adaptation to new requirements and stressors is of paramount importance. In this paper, we try to understand what are the main compound hazards, stressors and threats that influence bridges with short- and long-term impacts on their structural capacity and functionality and the impact of bridge closures on the network operability. We also prioritise the main drivers of bridge restoration and reinstatement, e.g. its importance, structural, resources, organisational factors. The loss of performance, driven by the redundancy and robustness of the bridge, is the first step to be considered in the overall process of resilience quantification. Resourcefulness is the other main component of resilience here analysed

Monitoring Technologies for Smart Cities and Civil Infrastructure Systems

The proportion of urban population in the world is expected to increase from 54% currently to 70% by 2050. A majority of Americans also reside in urban regions - according to the 2010 census 80% of Americans reside in urban areas. Given the large number of urban citizens in the world (and US) it is imperative that we identify solutions to improve the quality of life for urban residents and economic vitality of our cities. Studies to address and fulfill the needs of envisioned future smart city infrastructure should successfully integrate a range of engineering, humanities and sociological fields such as emerging communication technologies, Internet of Things (IoT), cyber security, cloud computing, intelligent transportation, infrastructure monitoring, analyzing tourism, theorizing structures of government and bureaucracy, project financing, public policy development and implementation. In this talk, we will first three overarching themes: (1) technologically advanced infrastructure with sensing and communication capability, (2) urban operations and services improved with better decisions using multilayered “big data”, and (3) utilization of technology for social, public policy, planning and governance to improve urban quality of life. Next, we will present a sampling of relevant U.S. research and education achievements in structural control and monitoring as compiled by U.S. Panel that are envisioned as concepts for smart cities. Finally, we will present our recent work at UCF CITRS in the area of structural health monitoring where novel technologies such as computer vision, deep learning have been developed for our existing and next generation of smart city infrastructure

Damage Detection With Time Series Modeling Using Ambient Vibration Data: Experimental Verifications

In this paper, structural condition assessment of a large scale 4-span bridge model using ambient vibration data is presented. An ARX model (Auto-Regressive models with eX-ogenous input) based damage detection methodology developed by the authors previously is used. Ambient vibration time histories are processed using Random Decrement (RD) to obtain pseudo-free response data. Then, ARX models are created for different sensor clusters by using the pseudo-free response of the structure. The output of each sensor in a cluster is used as an in-put to the ARX model to predict the output of the reference channel of that sensor cluster. After creating the ARX models for the healthy structure for each sensor cluster, these models are used for predicting the data from the damaged structure. The difference between the fit ratios is used as the Damage Feature (DF). Data from different damage cases are processed using the metho-dology and results are presented. It is shown that the methodology can successfully be used to detect and locate the applied damage in the structure

Evaluation Of A System Identification Method For Structural Health Monitoring: Theory And Examples

In this paper, the authors explore implementing an identification technique to real life structural health monitoring problems. The method presented in this paper is Observer/Kalman IDentification (OKID) which is used in conjunction with Eigensystem Realization Algorithm (ERA). After a review of theoretical background, the method is applied to two laboratory tests. In the first case, the authors analyze dynamic test results of three reinforced concrete beams with different fiber reinforced polymer configurations. While the beams are statically loaded until failure multiple input and multiple output data sets were collected and correlation between the capacity and the dynamic properties is explored. For the second case dynamic test data of a steel grid is analyzed. The grid is tested without any damage for both single span and two span configurations and dynamic properties identified using OKID/ERA are compared with their analytical counterparts

Ambient Vibration Data Analysis For Structural Identification And Global Condition Assessment

System identification is an area which deals with developing mathematical models to characterize the input-output behavior of an unknown system by means of experimental data. Structural health monitoring (SHM) provides the tools and technologies to collect and analyze input and output data to track the structural behavior. One of the most commonly used SHM technologies is dynamic testing. Ambient vibration testing is a practical dynamic testing method especially for large civil structures where input excitation cannot be directly measured. This paper presents a conceptual and reliable methodology for system identification and structural condition assessment using ambient vibration data where input data are not available. The system identification methodology presented in this study is based on the use of complex mode indicator functions (CMIFs) coupled with the random decrement (RD) method to identify the modal parameters from the output only data sets. CMIF is employed for parameter identification from the unscaled multiple-input multiple-output data sets generated using the RD method. For condition assessment, unscaled flexibility and the deflection profiles obtained from the dynamic tests are presented as a conceptual indicator. Laboratory tests on a steel grid and field tests on a long-span bridge were conducted and the dynamic properties identified from these tests are presented. For demonstrating condition assessment, deflected shapes obtained from unscaled flexibility are compared for undamaged and damaged laboratory grid structures. It is shown that structural changes on the steel grid structure are identified by using the unscaled deflected shapes. © 2008 ASCE