Multiscale Modelling and Analysis of Complex Nonlinear Dynamics Systems

The book’s emphasis on cutting-edge methodologies, such as machine learning-augmented modelling, concurrent multiscale coupling techniques, and quantum-classical hybrid computing, equips readers to address grand challenges in materials science, biological systems, and climate modelling. It discusses the potential of quantum computing for solving multiscale ordinary and partial differential equations.

The text:

• Integrates cutting-edge technologies like artificial intelligence-driven modelling, quantum computing, digital twins, and ethics in simulation.
• Addresses both data-driven and physics-based modelling, encompassing applications across multiple domains and scales—from molecular to geophysical systems.
• Bridges microscales, mesoscales, and macroscale dynamics using both physics-based and data-driven modelling approaches.
• Discusses mathematical modelling, computational methods, artificial intelligence tools, and domain-specific applications across physics, engineering, biology, and environmental systems.
• Includes detailed case studies such as aerospace crashworthiness, renewable energy systems, pandemic modelling, and smart manufacturing, showcasing how theoretical tools are applied to tangible, and high-impact problems.

It is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, mathematics, industrial and production engineering, and manufacturing engineering.