Alok Kumar Pandey – författare

Design Optimization Using Artificial Intelligence serves as an insightful resource for understanding the transformative role of Artificial Intelligence (AI) in optimizing design processes across a variety of fields. This book explores foundational concepts, advanced methodologies, and real-world applications, offering a comprehensive guide to leveraging AI for innovative design solutions.Covering a broad spectrum of topics, the book examines algorithmic advancements, machine learning techniques, and optimization strategies that enhance design efficiency and accuracy. It delves into AI's applications in sustainable energy systems, biomedical innovations, image processing, cyber-security, and other critical domains, showcasing its ability to solve complex challenges with precision and creativity.The content bridges theoretical foundations with practical implementations, incorporating case studies that highlight successful applications of AI-driven design optimization. Readers will gain valuable insights into state-of-the-art tools, programming techniques, and frameworks that drive advancements in intelligent design systems.Features:Explores AI-driven methodologies for enhancing design accuracy and efficiencyDiscusses advanced machine learning techniques and optimization algorithmsHighlights AI's applications in diverse fields such as energy systems, healthcare, image processing, and cyber-securityIncludes in-depth case studies to illustrate real-world implementations of AI in design optimizationInvestigates future trends and the potential of AI to transform traditional design processesTargeted at researchers, engineers, and students in the fields of artificial intelligence, computational science, and engineering, this book is an essential reference for anyone seeking to understand and utilize AI in the realm of design optimization. It provides the tools and knowledge necessary to harness AI's power for innovative, efficient, and intelligent design solutions.

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 approachesExplores nanofluid, hybrid nanofluid, and non-Newtonian fluid flow problems under multiple physical effectsIntegrates modern computational tools such as MATLAB® solvers, statistical optimization, and machine learning modelsDiscusses 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 technologiesOffers detailed insights into optimization and control strategies for enhancing thermal-fluid system performanceThis 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.

Fluid Flow and Heat Transfer Modeling – Computational Dynamics, Numerical Modelling, Flow Simulation presents a comprehensive and contemporary treatment of transport phenomena in complex engineering systems. Integrating fundamental conservation laws with advanced numerical techniques, the book explores fluid dynamics, heat and mass transfer, magnetohydrodynamics, nanofluid behavior, and non-Newtonian flow modeling.Bridging theory and computation, it highlights modern solution strategies including similarity transformations, finite element and finite volume methods, mesh-free RBF-FD techniques, and high-precision Runge–Kutta schemes. The volume further advances into optimization frameworks, artificial intelligence, machine learning, and ANN-based predictive modeling for enhanced thermal performance and real-time flow analysis.Designed for researchers, graduate students, and practicing engineers, this book provides both rigorous mathematical foundations and forward-looking computational tools essential for next-generation fluid flow simulation and intelligent thermal system design.