Del i serien Mathematical Engineering, Manufacturing, and Management Sciences

Multi-Scale Shock Wave Mechanics

Experimental, Computational, and AI Perspectives

Inbunden, Engelska, 2026

2 459 kr

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Multi-Scale Shock Wave Mechanics: Experimental, Computational, and AI Perspectives offers a comprehensive exploration of shock wave phenomena across multiple scales by integrating fundamental theory, high-fidelity computational modeling, advanced experimental diagnostics, and artificial intelligence techniques. This volume bridges classical shock wave physics with data-driven methodologies, providing a unified framework for understanding and predicting complex shock-driven processes in contemporary science and engineering.Structured into five cohesive parts, the book establishes theoretical and mathematical foundations, advances to experimental investigations with modern diagnostic techniques, and focuses on computational modeling including high-resolution simulations and instability analysis. A dedicated section explores AI's transformative role, demonstrating how machine learning and physics-informed neural networks enhance predictive accuracy and real-time analysis. The final part addresses practical applications in hypersonic aerospace systems. Combining rigorous formulations, computational tools, and AI innovations, this book provides insights into multi-scale shock dynamics, turbulence–shock interactions, and high-speed flow phenomena.This volume serves as an essential resource for researchers, academicians, and industry professionals in aerospace engineering, computational fluid dynamics, applied mathematics, and plasma physics. It consolidates current advances and offers a visionary outlook on future research directions in shock wave physics and AI-enhanced predictive modeling.

Produktinformation

Utgivningsdatum2026-10-13
Mått156 x 234 x undefined mm
FormatInbunden
SpråkEngelska
SerieMathematical Engineering, Manufacturing, and Management Sciences
Antal sidor344
FörlagTaylor & Francis Ltd
ISBN9781041109082

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Dr. Satyvir Singh is currently a Research Associate Fellow at the Institute of Applied and Computational Mathematics, RWTH Aachen University, Germany. He earned his Ph.D. in Computational Fluid Mechanics from the School of Mechanical and Aerospace Engineering, Gyeongsang National University, South Korea. He also holds an M.Tech. in Industrial Mathematics & Scientific Computing from the Indian Institute of Technology Madras, India, and an M.Sc. in Mathematics from CCS University Meerut, India. Prior to his current position, Dr. Singh served as a Senior Research Fellow at the Research Center for Aircraft Parts Technology, Gyeongsang National University, South Korea, and as a Research Fellow at Nanyang Technological University, Singapore. He has also served as an Assistant Professor at institutions in India, teaching mathematics at undergraduate and postgraduate levels. His research interests span computational fluid dynamics, high-order numerical methods, hydrodynamic instability, gas kinetic theory, heat and mass transfer, and computational biology, reflected in over 55 peer-reviewed articles with more than 950 citations.

Part I: Fundamentals and Theoretical Frameworks of Shock Waves Chapter 1: Introduction to Multi-Scale Shock Wave Mechanics Chapter 2: Advanced Mathematical Formulations of Shock Wave Propagation Chapter 3: Multi-Scale Kinetic Theories for Shock Wave Modeling Part II: Experimental and Laser Diagnostics of Shock Waves Chapter 4: High-Precision Experimental Techniques for Shock Wave Studies Chapter 5: Shock-Induced Phase Transitions in Materials Chapter 6: Shock Wave Interactions in Plasma and Laser-Generated Systems Chapter 7: Extreme Conditions: Ultra-High-Speed Impact and Detonation Waves Part III: Computational and Numerical Modeling of Shock Waves Chapter 9: Hybrid Continuum-Kinetic Models for Shock Wave Simulations Chapter 10: Shock-Induced Instabilities and Turbulence in Multi-Scale Flows Chapter 11: Nonlinear Wave Interactions and Shock Wave Focusing Part IV: Artificial Intelligence and Data-Driven Methods in Shock Wave Research Chapter 12: Machine Learning in Shock Wave Prediction and Optimization Chapter 13: Physics-Informed Neural Networks (PINNs) for Shock Wave Modeling Chapter 14: AI-Driven Uncertainty Quantification and Reliability Analysis Chapter 15: High-Performance Computing and Quantum Computing for Shock Dynamics Part V: Applications and Future Perspectives in Shock Wave Mechanics Chapter 16: Shock Waves in Aerospace and Hypersonic Vehicle Design Chapter 17: Shock-Induced Detonations and Explosive Dynamics Chapter 18: Biomedical and Medical Applications of Shock Waves Chapter 19: Astrophysical and Space Applications of Shock Waves Chapter 20: Future Trends and Emerging Research Directions in Shock Wave Mechanics