Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications
Language: English
Published by Taylor & Francis Ltd (Sales) Mai 2026, 2026
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Neuware - Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications; machine learning and deep learning methods can be applied and further developed to transform the available data into valuable information for engineers and decision makers.
Seller Inventory # 9781032308388
- Title
- Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications
- Author
- Carlo Rainieri
- Publisher
- Taylor & Francis Ltd (Sales) Mai 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1032308389
- ISBN 13
- 9781032308388
- Item weight
- 481 grams
- Dimensions
- 229x152x19 mm
Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications; machine learning and deep learning methods can be applied and further developed to transform the available data into valuable information for engineers and decision makers.
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About the Author
Mohammad Noori is a professor of mechanical engineering at California Polytechnic State University, San Luis Obispo; a fellow and life member of the American Society of Mechanical Engineering (ASME); and a recipient of the Japan Society for Promotion of Science Fellowship. His work in nonlinear random vibrations, especially hysteretic systems, in seismic isolation and application of artificial intelligence methods for structural health monitoring is widely cited. He has authored over 300 refereed papers, including over 150 journal articles; has published 15 scientific books, and 31 book chapters in archival volumes; has edited 15 technical books; and has been the guest editor of 15 journal volumes and proceedings. Noori was a co-founder of the National Institute of Aerospace, established through a $379 million 15-year NASA contract in partnership with NASA Langley Research Center. He has also received over $14 million in support of his research from the National Science Foundation (NSF), the Office of Naval Research (ONR), the National Sea Grant, and industry. He has supervised 24 postdoctoral, 26 PhD, and 53 MS projects. He has given over 20 keynote and 76 invited talks and lectures. He is the founding executive editor of a scientific journal, serves on the editorial board or as the associate editor of over 15 other journals, and has been a member of the scientific committee of numerous conferences. He directed the Sensors Program at the NSF in 2014, has been a distinguished visiting professor at several highly ranked universities in Europe and Asia, and serves as the scientific advisor for several organizations and technical firms. He was the dean of engineering at Cal Poly, served as a chaired professor and department head at North Carolina State University and Worcester Polytechnic Institute, and served as the chair of the national committee of mechanical engineering department heads. Noori has developed a unique online course, How to Write an Effective Research Paper, offered by Udemy.com and taken by over 9,000 students worldwide. Noori is an elected member of the Sigma Xi, Pi Tau Sigma, Chi-Epsilon, and Sigma Mu Epsilon honorary research societies. In 1996, Noori was invited by President Clinton’s Special Commission on Critical Infrastructure Protection and presented a testimony as a national expert on that topic. Noori is the founding editor of the Resilience and Sustainability in Civil, Mechanical, Aerospace and Manufacturing Engineering Systems Series of CRC Press/Taylor & Francis Group.
Carlo Rainieri is currently a research scientist at the National Research Council of Italy. His research interests are in the fields of civil structural health monitoring, operational modal analysis, and smart materials. He has been a number of national as well as international research projects focused on civil SHM. He is member of the editorial board of a number of scientific journals, such as Shock and Vibration, Infrastructures, Mathematical Problems in Engineering, and Advances in Civil Engineering, and he serves as guest editor for the Journal of Civil Structural Health Monitoring. Moreover, he was lead editor of the special issue on "Automated Operational Modal Analysis and Its Applications in Structural Health Monitoring" published in Shock and Vibration. In 2019, he received the International Operational Modal Analysis Conference (IOMAC) scientific award for his contribution to the development of operational modal analysis. He was chair of the 8th Civil Structural Health Monitoring Workshop (2021), and he was member of the scientific committee of a number of international conferences in the fields of operational modal analysis and SHM.
He is author of the first book on operational modal analysis that appeared in the literature (Operational Modal Analysis of Civil Engineering Structure: An Introduction and Guide for Applications, Springer) and of about 170 papers published in international peer-reviewed journals and national and international conference proceedings. His main achievements in the field of civil SHM have been the development of data-processing methods for vibration-based SHM applications, including a number of original automated operational modal analysis procedures and novel methods for compensation of environmental and operational influences on modal properties. Dr. Rainieri is also the founder and former CEO of S2X s.r.l. (www.s2x.it), a spin-off company of the University of Molise aimed at providing highly qualified solutions and services in the fields of civil SHM and output-only modal analysis of civil engineering structures.
Marco Domaneschi
is currently an assistant professor at the Department of Structural, Geotechnical and Building Engineering of Politecnico di Torino, where he teaches earthquake engineering and structural design courses. Formerly, he was a research associate and appointed professor of structural engineering at Politecnico di Milano. He is a professional structural engineer for special structures and serves as an R&D consultant in industrial manufacturing and mechanical engineering. He received his PhD from the University of Pavia (2006) and was a visiting researcher at several global universities. He currently serves as an associate editor and editorial board member for several international journals such as the Journal of Vibration and Control (SAGE) and Bridge Engineering (Institution of Civil Engineers, UK). He is also a member of several research associations such as the International Society of Structural Health Monitoring of Intelligent Infrastructure (ISHMII) and the International Association for Bridge Maintenance and Safety (IABMAS). He is also a reviewer for more than 40 international journals. He has been a speaker, sessions chair, editorial board member, and organizer in several international conferences. He received numerous awards for best presentations at conferences, and for research papers and activities. He supports/supported the coordination of several research projects and has/had scientific responsibility in numerous research projects. He has authored over 70 journal articles and 130 international conference papers. His research interests and activities include structural control and health monitoring, resilience and robustness of structures and communities, earthquake engineering and seismic risk, special structures, small- and large-scale simulations, emergency evacuation, and structural collapse analysis.
Vasilis Sarhosis
is an associate professor of structural engineering at the School of Civil Engineering, University of Leeds, UK. He holds both undergraduate and postgraduate degrees in civil engineering from the University of Leeds and worked as a consultant civil engineer in the UK. His main expertise lies in the development of advanced high-fidelity models of nonlinear response to quantify degradation and understand the long-term behavior of existing masonry infrastructure stock (e.g., bridges, tunnels, historic structures, and monuments) subjected to extreme loading conditions. Recently, he pioneered the development of the Cloud2DEM procedure to transform three-dimensional (3D) point clouds of complex structures obtained from photogrammetry and laser scanning to 3D discrete element models. The approach enables the realistic structural analysis of "as-is" masonry infrastructure in an accurate and computationally efficient manner. Dr. Sarhosis is a Chartered Engineer (CEng), Fellow of the Institute of Mechanical Engineering (FIMEchE), and Fellow of the Higher Education Academy (FHEA) in the UK. He is currently chairing the National Scientific Committee on the Analysis and Restoration of Structures of Architectural Heritage (ISCARSAH-UK), which is part of the International Council on Monuments and Sites (ICOMOS). He has edited a book on computational modeling of masonry structures using the discrete element method and published more than 100 peer-reviewed journal articles. His research has been cited more than 1,500 times, and his h-index is 22 (Scopus). For more information, please visit his website (https://www.sarhosis.com/home-1).
Wael A. Altabey
Dr. Wael A. Altabey is a full professor at department of Mechanical Engineering, Alexandria University, Alexandria, Egypt. Before that he was a research associate professor between 2018 to 2024 at International Institute for Urban Systems Engineering (IIUSE), Southeast University, Nanjing, China, and National and Local Joint Engineering Research Center for Basalt Fiber Production and Application Technology, Southeast University, Nanjing, Jiangsu, China, after completing a postdoctoral research fellowship for two years (2016-2018).
Since 2016 his researches have focused on the utilization of Artificial Intelligence (AI) based schemes for structural health monitoring (SHM) and Non-Destructive Testing (NDT) for damage classification, detection, diagnosis, prediction, dynamic response analysis, and Reliability evaluation in composite, and steel Structures (such as aircraft, wind turbines, pipes, bridges and industrial machines) at National and Local Joint Engineering Research Center for Basalt Fiber Production and Application Technology, Southeast University, Nanjing, Jiangsu, China. This is the only national R&D platform awarded by the National Development and Reform Commission in this industry with more than 30 national authorized patents. The center's international and national awards indicators have reached international and local leading levels and filling many technical gaps in China.
He participated in several research activities, which achieved from NSFC and private sectors. He listed in Stanford List of World's Top 2% Scientists from 2020, until now. He serves on various technical committees in several international conferences and workshops, guest editor of special Issues in several international scientific journals and on the editorial board of several international scientific journals in the field of artificial intelligence, mechanical, materials, and civil engineering. He a peer reviewer of more than 140 international scientific journals. He is an author and co-author of more than 110 high impact journal papers, 60 scientific conference papers and 50 chapters, 10 academic and research books, patent, and delivered over 40 invited talks.
His research interests: Smart and Nanomaterials; Composite Structures; Structural Health Monitoring (SHM); Artificial Intelligence (AI); Non-Destructive Testing (NDT); Digital Twins Model of Structural Behavior, System Identification; Damage Detection: Vibration-Based Techniques; Fiber Optical Sensing Technique, Structural Control; Structural Resilience and Reliability, Hysteretic Systems, Micro/Nano Electro Mechanical Systems (MEMS/ NEMS), and Energy Harvesting Model for Self-Powered Sensors.
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