Complex Engineering Systems - Modeling and Optimization offers an in-depth exploration of the foundational principles, advanced methodologies, and interdisciplinary applications essential for understanding and managing intricate engineering systems. Spanning mathematical modeling, numerical simulation, optimization strategies, and AI-assisted techniques, the book presents a rich blend of theory and real-world problem-solving tools. This comprehensive volume is tailored for researchers, professionals, and graduate students engaged in engineering, applied mathematics, and computational sciences.
Covering diverse themes-from system-of-systems behavior and multiphysics modeling to nanofluid dynamics, fractional heat transfer, queuing theory, and machine learning integration - the chapters collectively emphasize the interplay between complexity, adaptability, and innovation. The contributors shed light on modern challenges like cryogenic flow analysis, pressure sensing in microfluidics, MHD flow behavior, and AI-driven predictive modeling.
Dr. Satyvir Singh: Dr. Satyvir Singh is a Research Associate Fellow at the Institute of Applied and Computational Mathematics (ACoM), RWTH Aachen University, Germany (QS ranking #97). He earned his Ph.D. in Computational Fluid Mechanics from Gyeongsang National University, South Korea (QS ranking #301-350), with a thesis on 3D discontinuous Galerkin methods for Boltzmann-type gas kinetic equations. He has held research positions at Nanyang Technological University, Singapore (QS ranking #19), and Research Center for Aircraft Parts Technology, South Korea. Dr. Singh's research focuses on computational fluid dynamics, hydrodynamic instability, gas kinetic theory, and computational biology, with 50+ publications and 1 book. He has presented his work globally and recently co-led a research project on brain tumor dynamics at Jazan University, Saudi Arabia.
Dr. Mukesh Kumar Awasthi: Dr. Mukesh Kumar Awasthi, Assistant Professor at Babasaheb Bhimrao Ambedkar University, Lucknow, specializes in mathematical modeling of flow problems, including viscous potential flow, electro-hydrodynamics, and magneto-hydrodynamics. He has taught postgraduate courses such as Fluid Mechanics and Mathematical Methods. With over 125 research publications and 14 books, Dr. Awasthi is also the series editor of Artificial Intelligence and Machine Learning for Intelligent Engineering Systems (CRC Press). A recipient of multiple research awards and a UGC-funded project, he is listed among the top 2% influential researchers worldwide (Stanford University, 2022–2023).
