Computational and Mathematical Techniques for Heat Transfer and Fluid Dynamics offers an in-depth exploration of modern modeling, simulation, and optimization strategies for solving complex problems in thermal and fluid systems. This edited volume presents a diverse collection of chapters that blend classical theories with advanced computational methods and emerging technologies to address a wide spectrum of thermal-fluid phenomena.
Covering foundational concepts as well as cutting-edge research, the book introduces readers to the fundamental principles of heat transfer and fluid mechanics, followed by in-depth discussions on non-Newtonian fluid models, nanofluid and hybrid nanofluid behaviors, magnetic and chemical interactions, and micropolar and porous media flows. A distinctive feature of this volume is the integration of advanced numerical techniques--including similarity transformations, finite difference solvers, special functions, and fractional calculus--with optimization strategies and machine learning tools.
Special emphasis is placed on biomedical flows, multiphase systems, and the application of artificial intelligence in modeling and prediction. Readers will also find case studies related to energy systems, polymer processing, and chemical reactors, making this book highly relevant to both academic researchers and industry professionals.
This book:
- Introduces essential concepts of heat transfer and fluid dynamics using practical modeling approaches
- Explores nanofluid, hybrid nanofluid, and non-Newtonian fluid flow problems under multiple physical effects
- Integrates modern computational tools such as MATLAB(R) solvers, statistical optimization, and machine learning models
- Discusses the application of fractional calculus and exact analytical techniques for complex flow and thermal scenarios and presents real-world applications in microfluidics, biomedical systems, renewable energy, and advanced cooling technologies
- Offers detailed insights into optimization and control strategies for enhancing thermal-fluid system performance
This book is an essential resource for graduate students, researchers, engineers, and professionals in mechanical, chemical, aerospace, and applied mathematics fields who seek to deepen their understanding of computational heat transfer and fluid dynamics in both traditional and emerging applications.
Satya Ranjan Mishra is currently working as a Professor at the Department of Mathematics in Siksha O Anusandhan Deemed to be University. He has 19 years of teaching experience in both PG and UG level. He completed his PhD from Siksha O Anusandhan in 2013 and since then has actively engaged in his research work. His area of interest is Heat transfer, Magnetohydrodynamics, Porous media, etc. with the broad area of Fluid Dynamics. He has published nearly 250 papers in the international journals of repute, and all are either SCI or Scopus indexed that can be viewed in various databases like Scopus, Research gate, Google scholar, etc. With a huge citation of his work, he took a position of Top 2% World Scientists by Stanford University, USA in 4 consecutive years i.e., 2020-2023. He has also guided 13 research scholars, and six more students are working under his guidance. Dr. Mishra Delivered several lectures in various conferences and Faculty development program organized by Rajasthan Technical University, Rajasthan in 2019 on the topic "Introduction to MATLAB", FDP organized by Poornima Group of Institutions, Rajasthan on the topic "Numerical solutions using scientific tool MAPLE" in 2020 (online), Summer instructional School organized by NIT Arunachachal Pradesh on the topic "Linear Algebra" in the year 2020. As strength he has edited a book series in Springer Nature for the year 2020 as a leading Editor and also Editor/associate editor in several reputed international journals. Dr. Mishra's forthcoming book Learning Numerical Method using MATLAB is going to be published soon.
Apul Narayan Dev is currently working as an Associate Professor and Coordinator at the Centre for Data Science in Siksha O Anusandhan Deemed to be University, Bhubaneswar. He has 12 years of teaching experience in both PG and UG level. He did his M.Phil and Ph.D. from Gauhati University in 2011 and 2016 respectively. His area of interest is Basic Study of theoretical Plasmas, Degenerate and Non-degenerate Plasmas, Mathematical method, Fluid flow, etc. with the broad area of Plasmas and Fluid Dynamics. He has published nearly 45 papers in reputed international journals, and all are either SCI or Scopus indexed that can be viewed in various databases like Scopus, Research gate, Google scholar, etc. His book Shock wave Phenomena in Dusty Plasma is available in Amazon. He has also guided 1 research scholar, and four more students are working under his guidance. He has organized two International Conferences (AMSE-2019, AMSE-2022) and two international webinars (Maple-2020, Mathematica-2020). He also edited a SCOPUS index Conference Proceeding in AIP Publisher for the year 2022 as a leading Editor.
Alok Kumar Pandey is an Assistant Professor at the Department of Mathematics in Graphic Era (Deemed to be University), India. He obtained his PhD from Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India. His area of research is Computational Fluid Dynamics. He has published more than 60 research articles in International Journals. He was included in the World's Top 2% Scientists 2023 list (by Stanford University). He was awarded with Publons Peer Review Award in 2018. He is a certified reviewer of more than 100 international journals. He is currently the Editor for the Open Physics and Journal of Engineering Researcher and Lecturer, Associate Editor for the Journal of Advanced Research in Numerical Heat Transfer, and Journal of Advanced Research in Micro and Nano Engineering and serving as a member of the editorial board for journals such as Teknomekanik and SCIREA Journal of mathematics. His scientific metrics according to Google Scholar show h-index=30, Citations=2126 and i10-index=43.
Mukesh Kumar Awasthi has done his Ph.D. titled "Viscous Correction for the Potential Flow Analysis of Capillary and Kelvin-Helmholtz instability". He is working as an Assistant Professor in the Department of Mathematics at Babasaheb Bhimrao Ambedkar University, Lucknow. Dr. Awasthi is specialized in the mathematical modeling of flow problems. He has taught courses of Fluid Mechanics, Discrete Mathematics, Partial differential equations, Abstract Algebra, Mathematical Methods, and Measure theory to postgraduate students. He has acquired excellent knowledge in the mathematical modeling of flow problems, and he can solve these problems analytically as well as numerically. He has a good grasp of the subjects like viscous potential flow, electro-hydrodynamics, magneto-hydrodynamics, heat, and mass transfer. He has excellent communication skills and leadership qualities. He is self-motivated and responds to suggestions in a more convincing manner. Dr. Awasthi has qualified National Eligibility Test (NET) conducted on all India level in the year 2008 by the Council of Scientific and Industrial Research (CSIR) and got Junior Research Fellowship (JRF) and Senior Research Fellowship (SRF) for doing research. He has published 135 plus research publications (journal articles/books/book chapters/conference articles) in many national and international journals and conferences with reputed publishers. He has published 15 books. He is also a series editor of Artificial Intelligence and Machine Learning for Intelligent Engineering Systems published by CRC Press. He has attended many symposia, workshops, and conferences in mathematics as well as fluid mechanics. He has got the "Research Awards" consecutively four times from 2013-2016 by the University of Petroleum and Energy Studies, Dehradun, India. He has also received the start-up research fund for his project "Nonlinear study of the interface in multilayer fluid system" from UGC, New Delhi. He is also listed among the top 2% of influential researchers in the world, as prepared by Stanford University based on Scopus data for the years 2022 and 2023. His Orcid ID is 0000-0002-6706-5226.
