Structural Health Monitoring of Composite Structures with Artificial Intelligence

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.