Structural Reliability and Health Monitoring of Composite Structures with Artificial Intelligence offers a comprehensive review of the application of AI in the SHM of composite structures. Sections cover new developments such as the use of machine learning, deep learning, and artificial neural networks in SHM, while also illustrating 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.
In addition, 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 includes postgraduate students, academic researchers, and practicing engineers who are working in civil, mechanical, materials, and aerospace engineering.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. About the author - p. ix 7. Preface - p. xi 8. Acknowledgments - p. xv 9. 1. Composite materials concept - p. 1 10. 2. Design, manufacturing, and fabrication concepts for composite materials and structures - p. 25 11. 3. A fatigue damage model for composite structures - p. 45 12. 4. Structural health monitoring of composite structures - p. 85 13. 5. Probabilistic design of composite structures - p. 121 14. 6. Artificial intelligence based schemes for structural health monitoring of composite structures - p. 155 15. 7. Case studies: structural health monitoring of composite pipelines - p. 189 16. 8. Case studies: a damage identification in composite structures - p. 233 17. 9. Case studies: structural health monitoring of composite ducts - p. 259 18. 10. Case studies: structural health monitoring and probabilistic design analysis of composite plates - p. 281 19. Appendix A. Stress-strain theory in composite tubes - p. 307 20. Appendix B. Stress-strain components analysis - p. 323 21. Notations - p. 337 22. Bibliography - p. 341 23. Index - p. 369
Structural Reliability and Health Monitoring of Composite Structures with Artificial Intelligence offers a comprehensive review of the application of AI in the SHM of composite structures. Sections cover new developments such as the use of machine learning, deep learning, and artificial neural networks in SHM, while also illustrating 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.
In addition, 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 includes postgraduate students, academic researchers, and practicing engineers who are working in civil, mechanical, materials, and aerospace engineering.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. About the author - p. ix 7. Preface - p. xi 8. Acknowledgments - p. xv 9. 1. Composite materials concept - p. 1 10. 2. Design, manufacturing, and fabrication concepts for composite materials and structures - p. 25 11. 3. A fatigue damage model for composite structures - p. 45 12. 4. Structural health monitoring of composite structures - p. 85 13. 5. Probabilistic design of composite structures - p. 121 14. 6. Artificial intelligence based schemes for structural health monitoring of composite structures - p. 155 15. 7. Case studies: structural health monitoring of composite pipelines - p. 189 16. 8. Case studies: a damage identification in composite structures - p. 233 17. 9. Case studies: structural health monitoring of composite ducts - p. 259 18. 10. Case studies: structural health monitoring and probabilistic design analysis of composite plates - p. 281 19. Appendix A. Stress-strain theory in composite tubes - p. 307 20. Appendix B. Stress-strain components analysis - p. 323 21. Notations - p. 337 22. Bibliography - p. 341 23. Index - p. 369
