Structural Health Monitoring of Composite Structures with Artificial Intelligence

Nyhet

Häftad, Engelska, 2026

2 359 kr

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Structural Health Monitoring of Composite Structures with Artificial Intelligence offers a comprehensive review of the application of AI in the SHM of composite structures. The book’s objective is to bridge the gap between traditional SHM approaches and the integration of advanced AI techniques, providing readers with foundational knowledge on composite materials, manufacturing processes, mechanical behavior, and state-of-the-art SHM methodologies. The book is timely and significant as composite structures are witnessing increasing use in critical infrastructure, aerospace, and industry, where real-time, intelligent monitoring is crucial for safety and maintenance. It covers new developments such as the use of machine learning, deep learning, and artificial neural networks in SHM, and illustrates the integration of non-destructive testing (NDT) methods with AI algorithms. The content structure follows logical progression: from basic material concepts, design, manufacturing and fabrication, through damage and failure modes, advanced SHM monitoring, probabilistic design concepts, and AI based schemes for SHM. A full chapter is also dedicated to applied case studies in pipelines, ducts and plates) using analytical, numerical, and simulation tools (ANSYS, MATLAB). The book’s key audience will include postgraduate students, academic researchers, and practicing engineers, who are working in civil, mechanical, materials, and aerospace engineering.

Provides comprehensive integration of the fundamentals of composite materials, SHM, NDT, and AI all in one resource
Includes detailed practical case studies using real-world scenarios in pipelines, plates and wind turbine blades
Up-to-date inclusion of machine learning, deep learning, and neural networks in the SHM context
Contains comparative analysis of SHM/NDT methods and AI schemes
Contains explicit treatment of risk management and reliability assessment using AI and data fusion techniques

Produktinformation

Utgivningsdatum2026-07-07
Mått152 x 229 x undefined mm
FormatHäftad
SpråkEngelska
Antal sidor350
FörlagElsevier Science
ISBN9780443510946

Tillhör följande kategorier

Maskinteknik och material inom Naturvetenskap och teknik

Prf. 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 Natural Science Foundation of China (NSFC) and private sectors. He listed in Stanford List of World's Top 2% Scientists from 2020, until now. He is an IOP Associate Membership for 2025 (IOP Publishing-IOP Institute of Physics). 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 163 international scientific journals, He is an Organizing Member in several international scientific Centers includes members of professors, researchers, and students in mechanical, civil, electrical, chemical, and computer engineering, from nearly all continents (USA, UK, Japan, Egypt, Italy, China, Australia, Canada, Iran, Pakistan, Switzerland) to find and promote engineering solutions to help humanity overcome the continuing challenge of resilient seismic safety and to prevent earthquake disasters. He has a several individual international collaboration with several high talent researchers from different countries at USA, Europe and Asia. About his research, he is an author and co-author of more than 150 high impact journal papers, 60 scientific conference papers and 60 chapters, more than 10 academic and research books, more three patent and copyrights in the field of Artificial Intelligence based schemes for structural health monitoring, and delivered over 60 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.

1. COMPOSITE MATERIALS CONCEPT2. DESIGN, MANUFACTURING, AND FABRICATION CONCEPTS FOR COMPOSITE MATERIALS/STRUCTURES3. A FATIGUE DAMAGE MODEL FOR COMPOSITE STRUCTURES4. STRUCTURAL HEALTH MONITORING (SHM) OF COMPOSITE STRUCTURES5. PROBABILISTIC DESIGNS OF COMPOSITE STRUCTURES6. ARTIFICIAL INTELLIGENCE (AI) BASED SCHEMES FOR STRUCTURAL HEALTH MONITORING (SHM) OF COMPOSITE STRUCTURES7. CASE STUDIES: STRUCTURAL HEALTH MONITORING OF COMPOSITE PIPELINES8. CASE STUDIES: DAMAGE IDENTIFICATION IN COMPOSITE STRUCTURES9. CASE STUDIES: STRUCTURAL HEALTH MONITORING OF COMPOSITE DUCTS10. CASE STUDIES: STRUCTURAL HEALTH MONITORING AND PROBABILISTIC DESIGN ANALYSIS OF COMPOSITE PLATESAPPENDIX A STRESS-STRAIN THEORY IN COMPOSITE TUBESAPPENDIX B STRESS-STRAIN COMPONENTS ANALYSIS SUMMARY NOTATIONS REFERENCES