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Structural Motion Engineering
This innovative volume provides a systematic treatment of the basic concepts and computational procedures for structural motion design and engineering for civil installations. The authors illustrate the application of motion control to a wide spectrum of buildings through many examples. Topics covered include optimal stiffness distributions for building-type structures, the role of damping in controlling motion, tuned mass dampers, base isolation systems, linear control, and nonlinear control. The book's primary objective the satisfaction of motion-related design requirements such as restrictions on displacement and acceleration and seeks the optimal deployment of material stiffness and motion control devices to achieve these design targets as well as satisfy constraints on strength. The book is ideal for practicing engineers and graduate students.
Available Accelerated Bridge Construction Options for Short Span Bridges
By employing prefabricated bridge elements and systems, Accelerated Bridge Construction reduces on-site construction time and traffic disruptions, and enhances long-term performance. ABC is particularly advantageous for short-span bridges that are well-suited to standardized prefabrication. In such cases, the entire superstructure and substructure can often be constructed using prefabricated deck elements, modular decks, or systems that span the full bridge width. The construction methods can range from traditional crane installations to Self-Propelled Modular Transport units or slide-in techniques for moving the entire superstructures. This book introduces the concept of ABC and examines its application in the context of short-span bridge construction. It categorizes and details short-span bridges based on various criteria and evaluates the performance of the existing bridges. Decision-making processes regarding the adoption of ABC, choice of elements, systems, and construction methods are also discussed. Additionally, the book covers the inspection of short-span bridges and includes a design example.
Smart Sensors for Structural Health Monitoring
Smart sensors are technologies designed to facilitate the monitoring operations. For instance, power consumption can be minimized through on-board processing and smart interrogation algorithms, and state detection enhanced through collaboration between sensor nodes. Applied to structural health monitoring, smart sensors are key enablers of sparse and dense sensor networks capable of monitoring full-scale structures and components. They are also critical in empowering operators with decision making capabilities. The objective of this Special Issue is to generate discussions on the latest advances in research on smart sensing technologies for structural health monitoring applications, with a focus on decision-enabling systems. This Special Issue covers a wide range of related topics such as innovative sensors and sensing technologies for crack, displacement, and sudden event monitoring, sensor optimization, and novel sensor data processing algorithms for damage and defect detection, operational modal analysis, and system identification of a wide variety of structures (bridges, transmission line towers, high-speed trains, masonry light houses, etc.).
Structural Health Monitoring 2015
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.
Structural Health Monitoring Based on Data Science Techniques
The modern structural health monitoring (SHM) paradigm of transforming in situ, real-time data acquisition into actionable decisions regarding structural performance, health state, maintenance, or life cycle assessment has been accelerated by the rapid growth of “big data” availability and advanced data science. Such data availability coupled with a wide variety of machine learning and data analytics techniques have led to rapid advancement of how SHM is executed, enabling increased transformation from research to practice. This book intends to present a representative collection of such data science advancements used for SHM applications, providing an important contribution for civil engineers, researchers, and practitioners around the world.
Data Science in Engineering, Volume 10
Data Science in Engineering, Volume 10: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics, 2023, the tenth volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on: Novel Data-driven Analysis Methods Deep Learning Gaussian Process Analysis Real-time Video-based Analysis Applications to Nonlinear Dynamics and Damage Detection High-rate Structural Monitoring and Prognostics
Inverse Dynamics Problems
The inverse dynamics problem was developed in order to provide researchers with the state of the art in inverse problems for dynamic and vibrational systems. Contrasted with a forward problem, which solves for the system output in a straightforward manner, an inverse problem searches for the system input through a procedure contaminated with errors and uncertainties. An inverse problem, with a focus on structural dynamics, determines the changes made to the system and estimates the inputs, including forces and moments, to the system, utilizing measurements of structural vibration responses only. With its complex mathematical structure and need for more reliable input estimations, the inverse problem is still a fundamental subject of research among mathematicians and engineering scientists. This book contains 11 articles that touch upon various aspects of inverse dynamic problems.
Data Science in Engineering, Volume 9
Data Science and Engineering Volume 9: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics, 2021, the ninth volume of nine from the Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on: Data Science in Engineering Applications Engineering Mathematics Computational Methods in Engineering
Recurrent Neural Networks
The text discusses recurrent neural networks for prediction and offers new insights into the learning algorithms, architectures, and stability of recurrent neural networks. It discusses important topics including recurrent and folding networks, long short-term memory (LSTM) networks, gated recurrent unit neural networks, language modeling, neural network model, activation function, feed-forward network, learning algorithm, neural turning machines, and approximation ability. The text discusses diverse applications in areas including air pollutant modeling and prediction, attractor discovery and chaos, ECG signal processing, and speech processing. Case studies are interspersed throughout the b...
