Bridge Condition Assessment Using Dynamic Response Collected Through Wireless Sensor Networks
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Bridge Condition Assessment Using Dynamic Response Collected Through Wireless Sensor Networks
With a large inventory of deficient and aging bridges in the United States, this research focused on developing dynamic response based health monitoring system of prestressed box beam (PSBB) bridges that will provide more realistic and cost-efficient results. The hypothesis is based on the assumption that the dynamic response is a sensitive and important indicator of the physical integrity and condition of a structure. Two wireless sensor networks (WSNs) were deployed for the collection of real-time acceleration response of a 25-year old PSBB bridge under trucks with variable loads and speeds. The acceleration response of the bridge at its newest condition was collected from the dynamic simulations of its full-scale finite element (FE) models mimicking field conditions. The FE model was validated using experimental and theoretical methods. The acceleration data in time domain were transformed into frequency domain using Fast Fourier Transform to determine peak amplitudes and their corresponding fundamental frequencies for the newest and the current condition of the bridge. The analyses and comparisons of the bridge dynamic response between the newest and the current bridge interestingly indicate a 37% reduction in its fundamental frequency over its 25 years of service life. This reduction has been correlated to the current condition rating of the bridge to develop application software for quick and efficient condition assessment of a PSBB bridge. The application software can instantly estimate overall bridge condition rating when used with the WSN deployed on a PSBB bridge under vehicular loads. The research outcome and the software is expected to provide a cost-effective solution for assessing the overall condition of a PSBB bridge, which helps to reduce maintenance costs and provide technologically improved bridge maintenance service.
Bridge Condition Assessment and Load Rating Using Dynamic Response
This report describes a method for the overall condition assessment and load rating of prestressed box beam (PSBB) bridges based on their dynamic response collected through wireless sensor networks (WSNs). Due to a large inventory of deficient and aging bridges in the United States, the health monitoring of bridges can be very expensive; therefore, new tools for quick, efficient and response-based condition assessment and load rating of bridges will be helpful. The hypothesis is based on the assumption that the health of a bridge is associated with its vibration signatures under vehicular loads. Two WSNs were deployed on a 25-year old PSBB bridge under trucks with variable loads and speeds, and its dynamic response was collected at the current condition. The acceleration response of the bridge at its newest condition was collected from dynamic simulations of its full-scale finite element analysis (FEA) models mimicking field conditions. The FEA bridge model was validated by the field testing and numerical analysis. The acceleration data in time domain were transformed into frequency domain using Fast Fourier Transform to determine peak amplitudes and corresponding fundamental frequencies for the newest and current conditions. The analyses and comparisons of the bridge dynamic response between the newest and the current bridge interestingly indicate a 37% reduction in its fundamental frequency over 25 years of service life. This frequency reduction is linked to the reduction in condition rating of the current bridge. The analysis data, bridge structural dynamics and bridge geometric parameters have been used to calculate the in-service stiffness of the bridge to estimate its load bearing capacity. Using the results and algorithms from this research, application software is developed to instantly estimate the overall condition rating and load bearing capacity of a PSBB bridge under vehicular loads. The research outcome and the software will help in performing quick and cost-effective condition assessment and load rating of PSBB bridges, and may provide a better ability to plan replacements and develop load ratings.
Bridge Safety, Maintenance, Management, Life-Cycle, Resilience and Sustainability
Bridge Safety, Maintenance, Management, Life-Cycle, Resilience and Sustainability contains lectures and papers presented at the Eleventh International Conference on Bridge Maintenance, Safety and Management (IABMAS 2022, Barcelona, Spain, 11–15 July, 2022). This e-book contains the full papers of 322 contributions presented at IABMAS 2022, including the T.Y. Lin Lecture, 4 Keynote Lectures, and 317 technical papers from 36 countries all around the world. The contributions deal with the state-of-the-art as well as emerging concepts and innovative applications related to the main aspects of safety, maintenance, management, life-cycle, resilience, sustainability and technological innovations of bridges. Major topics include: advanced bridge design, construction and maintenance approaches, safety, reliability and risk evaluation, life-cycle management, life-cycle, resilience, sustainability, standardization, analytical models, bridge management systems, service life prediction, structural health monitoring, non-destructive testing and field testing, robustness and redundancy, durability enhancement, repair and rehabilitation, fatigue and corrosion, extreme loads, needs of bridge owners, whole life costing and investment for the future, financial planning and application of information and computer technology, big data analysis and artificial intelligence for bridges, among others. This volume provides both an up-to-date overview of the field of bridge engineering and significant contributions to the process of making more rational decisions on bridge safety, maintenance, management, life-cycle, resilience and sustainability of bridges for the purpose of enhancing the welfare of society. The volume serves as a valuable reference to all concerned with and/or involved in bridge structure and infrastructure systems, including students, researchers and practitioners from all areas of bridge engineering.