Failure Modelling of Textile Composites

Erscheinungsjahr 2027
ISBN: 978-3-032-33796-2
Verlag: Springer

Buch, Englisch, 207 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Engineering Materials

Failure Modelling of Textile Composites offers a thorough and organized summary of the models, procedures, and mechanisms governing the failure behavior of composite materials based on textiles. Advanced textile composites are expanding quickly in the automotive, aerospace, defence, and energy sectors. As a result, it is now essential to comprehend and forecast how these materials will fail under complicated loading scenarios in order to ensure safe and effective design. Through a thoughtful blending of theoretical underpinnings, computational modeling techniques, and practical observations, this book fills that gap. The book starts with the basics of textile-reinforced composites and then goes on to examine how the complex structures of textile fabric affect their mechanical response. With the help of experimental findings and microstructural considerations, the development of damage is thoroughly examined, ranging from matrix cracking and fiber breaking to interfacial debonding and delamination.  Advanced testing procedures and characterisation techniques that are essential for model calibration and validation are presented in dedicated chapters. The book's main focus is on continuum damage mechanics (CDM) models specifically designed for textile composites, as well as phenomenological and analytical approaches. After that, it moves into numerical and multiscale modelling techniques, showing how cohesive zone models, finite element analyses, and representative volume elements (RVEs) are used to portray the intricate, hierarchical character of failure. Validation studies and real-world case examples from automotive, aerospace, and protective applications support the debate and show how theoretical models correspond to actual performance. Concluding with emerging trends, the book highlights the integration of machine learning, digital twins, and data-driven approaches for failure prediction and structural health monitoring. It also explores future directions such as sustainable textile composites and hybrid reinforcement systems. It offers a hybrid deep learning method that combines a dual-input Convolutional Neural Network (CNN) for mechanical property prediction with a Deep Q-Network (DQN) for optimization.

Zielgruppe

Research

Autoren/Hrsg.

Dixit, Anurag

Tevatia, Abhishek

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde

Inhaltsverzeichnis

Modelling Strategies for Textile Reinforced Composites.- Failure Mechanisms in Textile Composites.- Experimental Characterization of Damage and Failure.- Analytical and Continuum Damage Modelling Approaches.- Numerical and Multiscale Simulation Strategies.- Validation, Benchmarking, and Case Studies.- Emerging Directions and Future Outlook.

Über Autor(innen)

Dr. Anurag Dixit is an Assistant Professor in Department of Mechanical Engineering at G.B. Pant DSEU Campus, New Delhi (formerly G.B. Pant Government Engineering College, New Delhi). He has over fifteen years of teaching and research experience. His research interests include finite element analysis of textile composites and the large deformation behavior of metals and composites under low, medium, and high strain-rate loading conditions. His research has significant applications in the design and safety of engineering systems for defence, aerospace, mobility, marine industries, and metal-forming processes. Dr. Dixit has published more than 30 research articles in reputed international journals indexed in the Science Citation Index (SCI).

As Co-Principal Investigator, he successfully completed a Defence Research and Development Organisation (DRDO), Government of India-funded research project worth ?37 lakhs. He has served as Editor of three Springer books, namely Additive Manufacturing for Biomedical Applications, Biodegradable Metallic Materials: Design, Development and Characterization, and High-Performance Textile Composites. In addition, he serves as a reviewer for several leading international journals and actively contributes to advancing research in the fields of advanced materials, manufacturing technologies, and computational mechanics. In addition, he serves as a reviewer for several leading international journals and actively contributes to advancing research in the fields of advanced materials, manufacturing technologies, and computational mechanics. 

Dr. Abhishek Tevatia is an Assistant Professor in the Department of Mechanical Engineering at Netaji Subhas University of Technology (NSUT), New Delhi, with over 15 years of experience in teaching, research, and academic administration. He earned his Ph.D. in Mechanical Engineering in 2018, specializing in fatigue crack growth in metal matrix composites. His research interests include computational modeling, finite element fatigue analysis, composite failure modeling, and uncertainty analysis. Dr. Tevatia has published over 39 research papers and 7 book chapters with reputed publishers including Springer, Elsevier, IMechE, and Taylor & Francis. He has received the Young Achiever Award (2022) and Commendable Research Awards (2021–22 & 2022–23), and currently serves as Joint Controller of Examination at NSUT while actively contributing to curriculum development and NEP-2020 implementation.