Mathematical Solutions for Complex Engineering Systems | 46.28 MB
Title: Mathematical Solutions for Complex Engineering Systems
Author: Satyvir Singh, Mukesh Kumar Awasthi
Category: Nonfiction, Science & Nature, Science, Physics, Mechanics, Energy, Technology
Language: English | 392 Pages | ISBN: 146128340X
Description:
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 disciplines. This book brings together a diverse collection of research contributions that highlight: Deterministic, stochastic, linear, and nonlinear models essential for analyzing multi-physical systems, from fluid dynamics to reliability engineering. Cutting-edge methods such as finite element analysis, boundary element methods, Keller box techniques, and machine learning-driven modeling for solving complex engineering problems. Case studies on nuclear power plant reliability, eco-epidemiology, nanofluid heat transfer, and pesticide impact on agricultural sustainability. Novel mathematical frameworks, including fractional Taylor wavelets, B-spline methods, and variational principles, for tackling nonlinear differential equations. Advanced concepts such as tunnel mathematics, meshfree methods, and high-resolution computational fluid dynamics (CFD) models for solving contemporary engineering challenges. Designed for researchers, engineers, and graduate students, this book provides a robust foundation in mathematical techniques and their practical applications. With contributions from leading experts, it offers a unique blend of theoretical depth and computational efficiency, making it an essential reference for tackling modern engineering complexities. This book explores advanced modeling, computational methods and optimization strategies for real-world engineering challenges. It covers deterministic and stochastic models, cutting-edge machine learning techniques and their practical applications.
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 disciplines. This book brings together a diverse collection of research contributions that highlight: Deterministic, stochastic, linear, and nonlinear models essential for analyzing multi-physical systems, from fluid dynamics to reliability engineering. Cutting-edge methods such as finite element analysis, boundary element methods, Keller box techniques, and machine learning-driven modeling for solving complex engineering problems. Case studies on nuclear power plant reliability, eco-epidemiology, nanofluid heat transfer, and pesticide impact on agricultural sustainability. Novel mathematical frameworks, including fractional Taylor wavelets, B-spline methods, and variational principles, for tackling nonlinear differential equations. Advanced concepts such as tunnel mathematics, meshfree methods, and high-resolution computational fluid dynamics (CFD) models for solving contemporary engineering challenges. Designed for researchers, engineers, and graduate students, this book provides a robust foundation in mathematical techniques and their practical applications. With contributions from leading experts, it offers a unique blend of theoretical depth and computational efficiency, making it an essential reference for tackling modern engineering complexities. This book explores advanced modeling, computational methods and optimization strategies for real-world engineering challenges. It covers deterministic and stochastic models, cutting-edge machine learning techniques and their practical applications.
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