1st Edition

Mathematical Solutions for Complex Engineering Systems

Edited By Satyvir Singh, Mukesh Kumar Awasthi Copyright 2026
392 Pages 102 Color & 8 B/W Illustrations
by River Publishers

In an era where engineering challenges are becoming increasingly multifaceted, Mathematical Solutions for Complex Engineering Systems serves as a comprehensive guide bridging the gap between theory and real-world applications. This book explores advanced mathematical modeling techniques, computational approaches, and optimization strategies that drive innovation across various engineering... Read more

Chapter 1: Recent Innovations and Advances in Mathematical Modeling for Engineering Systems

Chapter 2: A Study of Approximation Techniques used to Solve Queueing Models that Arise in Optimizing Complex Engineering Systems

Chapter 3: Stochastic Modeling in Engineering Systems: A study of a Nuclear Power Plant System

Chapter 4: Nonlinear Dynamics and Chaos in Engineering Systems: Through an Epidemic Model

Chapter 5: Eco-epidemiological Analysis of Plant–Herbivore Interactions: The Allee Effect and Time-dependent Dynamics

Chapter 6: Impacts of Pesticides and External Interventions on Crop Production: A Modeling Approach

Chapter 7: Tensor Foundations of Tunnel Mathematics

Chapter 8: Boundary Element Analysis for MHD Stokes Flow through a Microchannel Exhibiting Surface Roughness

Chapter 9: Numerical Investigation of Non-Darcy MHD Boundary Layer Nanofluids Flow Over a Non-linear Stretching Surface

Chapter 10 : Extended Hydrodynamic Models for Rayleigh–Brillouin Scattering in Polyatomic Rarefied Gases: A Comparative Study

Chapter 11:  Nodal Discontinuous Galerkin Framework for Solving Grad-17 Moment Equations in a Rarefied Regime

Chapter 12: Exploring the Method of Fundamental Solutions for Nonhomogeneous and Nonlinear Partial Differential Equations

Chapter 13: A Fractional order Taylor Wavelets Approach for the Numerical Simulation of Fractional Variational Problems

Chapter 14: New Fourth-order Efficient Numerical Solutions of the Klein–Gordon Equation

Chapter 15: Numerical Approximation of the Sine–Gordon Equation by Using the Hybrid B-spline Differential Quadrature Method

Chapter 16: An Overview of High-resolution Schemes in the OpenFOAM Toolkit

Biography

Dr. Satyvir Singh is a Research Associate Fellow at the Institute of Applied and Computational Mathematics, RWTH Aachen University, Germany. He obtained his Ph.D. in Computational Fluid Mechanics from Gyeongsang National University, South Korea, where he developed 3D discontinuous Galerkin methods for solving Boltzmann-type gas kinetic equations. He has held research positions at Nanyang Technological University, Singapore, and the Research Center for Aircraft Parts Technology in South Korea. His expertise spans computational fluid dynamics, high-order numerical methods, gas kinetic theory, and hydrodynamic instability. Dr. Singh has authored over 50 research articles with more than 700 citations and has presented his work globally. He has also received research funding as Co-PI for a project on brain tumor dynamics at Jazan University, Saudi Arabia.

Dr. Mukesh Kumar Awasthi is an Assistant Professor in the Department of Mathematics at Babasaheb Bhimrao Ambedkar University, Lucknow. Specializing in mathematical modeling of flow problems, he has expertise in viscous potential flow, electro-hydrodynamics, magneto-hydrodynamics, and heat and mass transfer. Dr. Awasthi has published over 135 research works, including books and journal articles, and has served as a series editor for CRC Press. He has received multiple research awards and secured funding for his project on nonlinear fluid interfaces. Recognized among the top 2% of researchers worldwide by Stanford University in 2022 and 2023, he continues to contribute significantly to computational mathematics and engineering applications.