Download Free The Remote Continuous Structural Health Monitoring Of The East 12th Street Bridge Book in PDF and EPUB Free Download. You can read online The Remote Continuous Structural Health Monitoring Of The East 12th Street Bridge and write the review.

Of the approximately 25,000 bridges in Iowa, 28% are classified as structurally deficient, functionally obsolete, or both. The state of Iowa thus follows the national trend of an aging infrastructure in dire need of repair or replacement with a relatively limited funding base. Therefore, there is a need to develop new materials with properties that may lead to longer life spans and reduced life-cycle costs. In addition, new methods for determining the condition of structures are needed to monitor the structures effectively and identify when the useful life of the structure has expired or other maintenance is needed. High-performance steel (HPS) has emerged as a material with enhanced weldability, weathering capabilities, and fracture toughness compared to conventional structural steels. In 2004, the Iowa Department of Transportation opened Iowa's first HPS girder bridge, the East 12th Street Bridge over I-235 in Des Moines, IA. The objective of this project was to evaluate HPS as a viable option for use in Iowa bridges with a continuous structural health monitoring (SHM) system. The scope of the project included documenting the construction of the East 12th Street Bridge and concurrently developing a remote, continuous SHM system using fiber-optic sensing technology to evaluate the structural performance of the bridge. The SHM system included bridge evaluation parameters, similar to design parameters used by bridge engineers, for evaluating the structure. Through the successful completion of this project, a baseline of bridge performance was established that can be used for continued long-term monitoring of the structure. In general, the structural performance of the HPS bridge exceeded the design parameters and is performing well. Although some problems were encountered with the SHM system, the system functions well and recommendations for improving the system have been made.
This book offers an in-depth investigation into the complexities of long-term structural health monitoring (SHM) in civil structures, specifically focusing on the challenges posed by small data and environmental and operational changes (EOCs). Traditional contact-based sensor networks in SHM produce large amounts of data, complicating big data management. In contrast, synthetic aperture radar (SAR)-aided SHM often faces challenges with small datasets and limited displacement data. Additionally, EOCs can mimic the structural damage, resulting in false errors that can critically affect economic and safety issues. Addressing these challenges, this book introduces seven advanced unsupervised learning methods for SHM, combining AI, data sampling, and statistical analysis. These include techniques for managing datasets and addressing EOCs. Methods range from nearest neighbor searching and Hamiltonian Monte Carlo sampling to innovative offline and online learning frameworks, focusing on data augmentation and normalization. Key approaches involve deep autoencoders for data processing and novel algorithms for damage detection. Validated using simulated data from the I-40 Bridge, USA, and real-world data from the Tadcaster Bridge, UK, these methods show promise in addressing SAR-aided SHM challenges, offering practical tools for real-world applications. The book, thereby, presents a comprehensive suite of innovative strategies to advance the field of SHM.
Proceedings Annie Conference, November 2006, St. Louis, Missouri. The newest volume in this series presents refereed papers in the following categories and their applications in the engineering domain: Neural Networks; Complex Networks; Evolutionary Programming; Data Mining; Fuzzy Logic; Adaptive Control; Pattern Recognition; Smart Engineering System Design. These papers are intended to provide a forum for researchers in the field to exchange ideas on smart engineering system design.
Structural health monitoring (SHM) uses one or more in situ sensing systems placed in or around a structure, providing real-time evaluation of its performance and ultimately preventing structural failure. Although most commonly used in civil engineering, such as in roads, bridges, and dams, SHM is now finding applications in other engineering envir
This volume gathers the latest advances, innovations, and applications in the field of structural health monitoring (SHM) and more broadly in the fields of smart materials and intelligent systems, as presented by leading international researchers and engineers at the 10th European Workshop on Structural Health Monitoring (EWSHM), held in Palermo, Italy on July 4-7, 2022. The volume covers highly diverse topics, including signal processing, smart sensors, autonomous systems, remote sensing and support, UAV platforms for SHM, Internet of Things, Industry 4.0, and SHM for civil structures and infrastructures. The contributions, which are published after a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaboration among different specialists.
Proceedings of the Tenth International Workshop on Structural Health Monitoring, September 1–3, 2015. Selected research on the entire spectrum of structural health techniques and areas of applicationAvailable in print, complete online text download or individual articles. Series book comprising two volumes provides selected international research on the entire spectrum of structural health monitoring techniques used to diagnose and safeguard aircraft, vehicles, buildings, civil infrastructure, ships and railroads, as well as their components such as joints, bondlines, coatings and more. Includes special sections on system design, signal processing, multifunctional materials, sensor distribution, embedded sensors for monitoring composites, reliability and applicability in extreme environments. The extensive contents can be viewed below.
This two-volume book set contains over 425 papers. While offering investigations into how sensors, networks, and signaling systems are used in dozens of civil and military applications, a special feature of this book is its exploration of how to enable intelligent life-cycle health management for the industrial internet of things. It demonstrates how machine-learning and stochastic methods add value to SHM data by taking into account changing environments and conditional events. It offers new insights on interactions between SHM data and big data for improving the safety and integrity of monitored structures. Information is also presented on how SHM sensing interfaces with smart and functional materials operating in dynamic systems. A large number of SHM applications are explained, including additive manufacturing, advanced composites, actuators, corrosion, machinery, power plants, piping, robotics, underground infrastructure, and many more.Chapters in the book are edited presentations from a September 2019 Workshop at Stanford University co-sponsored by the U.S. Air Force Office of Scientific Research and the Office of Naval Research.
Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations contains lectures and papers presented at the Tenth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2020), held in Sapporo, Hokkaido, Japan, April 11–15, 2021. This volume consists of a book of extended abstracts and a USB card containing the full papers of 571 contributions presented at IABMAS 2020, including the T.Y. Lin Lecture, 9 Keynote Lectures, and 561 technical papers from 40 countries. The contributions presented at IABMAS 2020 deal with the state of the art as well as emerging concepts and innovative applications related to the main aspects of maintenance, safety, management, life-cycle 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 sustainability, standardization, analytical models, bridge management systems, service life prediction, maintenance and management strategies, structural health monitoring, non-destructive testing and field testing, safety, resilience, robustness and redundancy, durability enhancement, repair and rehabilitation, fatigue and corrosion, extreme loads, and application of information and computer technology 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 maintenance, safety, management, life-cycle sustainability and technological innovations of bridges for the purpose of enhancing the welfare of society. The Editors hope that these Proceedings will serve as a valuable reference to all concerned with bridge structure and infrastructure systems, including engineers, researchers, academics and students from all areas of bridge engineering.