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Elsevier

Books in General engineering

Our General Engineering collection provides a broad foundation across multiple engineering disciplines, including fundamentals, design principles, and interdisciplinary innovations. It supports researchers, students, and professionals with essential tools and insights to tackle complex engineering challenges, foster innovation, and integrate emerging technologies such as AI, sustainability practices, and smart manufacturing.

  • Engineering Materials for 3D Printing

    Synthesis, Functionalization to Applications
    • 1st Edition
    • Rupinder Singh + 3 more
    • English
    Engineering Materials for 3D Printing: Synthesis, Functionalization to Applications delves into the transformative world of additive manufacturing, covering the development and characterization of polymer-based materials crafted through processes such as extrusion, sol-gel, and pulverization. Over the past three decades, 3D printing has revolutionized the creation of functional prototypes, utilizing an array of materials like thermoplastics, resins, metals, and alloys. This book explores the advantages of 3D printing over conventional manufacturing, emphasizing its potential for structural and non-structural engineering applications. It stands out for its focus on meta-structure properties, offering insights into the fabrication of engineering prototypes.While existing literature extensively covers manufacturing processes, this work bridges the gap by exploring 3D printable materials for diverse engineering uses.

  • Network-Constrained Data-Driven Control of High-Speed Railway Systems

    Adaptive and Learning-Based Approaches
    • 1st Edition
    • Deqing Huang + 1 more
    • English
    Network-Constrained Data-Driven Control of High-Speed Rail Systems: Adaptive and Learning-Based Approaches addresses critical challenges in high-speed railway (HSR) operational control systems, focusing on enhancing safety, efficiency, and automation in an era of rapid network expansion. The book introduces a transformative framework for data-driven adaptive control and multi-train cooperative control under dynamic network constraints. It integrates next-generation 5G-R communication to enable real-time train-to-train (T2T) coordination, reducing dependency on fixed infrastructure and addressing vulnerabilities like faded channels and interference. By combining rigorous theoretical analysis with simulations, the book proposes solutions to improve operational precision, resilience against disruptions, and transportation capacity.This resource is helpful for researchers, engineers, and graduate students in high speed railway control systems, offering innovative strategies to advance autonomous operations and meet the demands of high-density, high-speed rail networks

  • INTELLIGENT FAULT DIAGNOSIS AND PROGNOSIS FOR INDUSTRIAL SYSTEMS

    CROSS-DOMAIN, ZERO-SAMPLE, AND DEGRADATION MODELING METHODS
    • 1st Edition
    • Hongpeng Yin + 2 more
    • English
    Industrial Fault Diagnosis and Remaining Useful Life Prediction: Cross-Domain, Zero-Sample, and Degradation Modeling Methods introduces zero-sample learning methods that enable fault diagnosis and Predict Remaining Useful Life (RUL) without the need for labelled fault data. This is particularly valuable in industrial settings where labelled data is scarce or unavailable. Offers step-by-step guidance on implementing zero-shot learning models using real industrial data, reducing the learning curve for practitioners; includes real-world industrial case studies to demonstrate the application of zero-sample learning techniques in various industries, such as manufacturing, energy, and transportation. Such case studies provide readers with actionable insights and practical solutions. The book covers advanced methodologies for predicting the remaining useful life of industrial equipment, supporting readers in optimizing maintenance schedules, reducing downtime and extending the lifespan of critical assets. Covers state-of-the-art algorithms, including deep learning, transfer learning and domain adaptation, tailored for zero-sample scenarios. These tools empower readers to develop robust fault diagnosis and RUL prediction systems, enhancing predictive maintenance capabilities and ensuring the reliability of industrial systems.

  • Machine Learning in the Analysis of Deformation, Fatigue and Fracture in Solids

    • 1st Edition
    • Guozheng Kang + 4 more
    • English
    Machine Learning in the Analysis of Solid Deformation, Fatigue and Fracture fills a clear gap in literature by applying machine learning to deformation, fatigue, and fracture analysis in solid mechanics. The book’s focus on complex mechanisms and coupling phenomena, discussed with practical examples, makes it a valuable resource for advanced researchers. Practical examples and case studies enable readers to understand both the underlying engineering problems and the application of machine learning methods to enhance fatigue life prediction analysis for solid materials and structures.

  • Foundations of Mathematical Modeling and Analysis in Engineering

    • 1st Edition
    • A. Ted Watson
    • English
    Foundations of Mathematical Modeling and Analysis in Engineering offers a comprehensivepresent... of the mathematical principles underpinning modern engineering and the quantitative sciences, and develops mathematical modeling as a foundational intellectual discipline. Designed for graduate and advanced undergraduate students, and accessible to seasoned professionals, it provides the means to develop and employ mathematical representations of physical processes and systems.

  • The Control of Multiple Unmanned Aerial Vehicles

    Synthesis, Functionalization to Applications
    • 1st Edition
    • Mingyang Xie + 2 more
    • English
    The Control of Multiple Unmanned Aerial Vehicles: Synthesis, Functionalization to Applications provides readers with a unified framework to address the challenges of multi-UAV target encirclement tracking control. This is achieved by comprehensively integrating the concepts of dynamic modelling, state and disturbance estimation, guidance law design, distributed control, obstacle avoidance and reinforcement learning-based formation tracking control with multi-UAV encirclement tracking systems. The book provides practical insight and solutions to the challenges of multi-UAV use, including limited sensing, communication constraint, wind disturbances and obstacle and collision avoidance, enabling readers to effectively apply the concepts to their work or research. Cutting-edge control techniques and advanced theories are explored, including robust distributed control, adaptive neural network approximation, reinforcement learning and multi-agent systems, presenting readers with state-of-the-art methodologies from which to develop practical applications of UAV formation. Each guidance and control method presented in the book is accompanied by a thorough comprehensive analysis to ensure that each is theoretically grounded. The book ensures transparency by providing open-access simulation codes, allowing readers to easily access and reproduce presented results.

  • Numerical Methods

    Using MATLAB
    • 5th Edition
    • George Lindfield + 1 more
    • English
    Numerical Methods Using MATLAB®, Fifth Edition continues to provide a clear and rigorous introduction to a wide range of numerical methods that have practical applications. The authors’ approach is to integrate MATLAB with numerical analysis in a way which adds clarity to the numerical analysis and develops familiarity with MATLAB. MATLAB graphics and numerical output are used extensively to clarify complex problems and give a deeper understanding of their nature. The text provides an extensive reference providing numerous useful and important numerical algorithms that are implemented in MATLAB to help researchers analyze a particular outcome.By using MATLAB it is possible for the readers to tackle some large and difficult problems and deepen and consolidate their understanding of problem solving using numerical methods. Many worked examples are given together with exercises and solutions to illustrate how numerical methods can be used to study problems that have applications in the biosciences, chaos, optimization and many other fields. The text will be a valuable aid to people working in a wide range of fields, such as engineering, science and economics.

  • Deep Learning for Image Recognition

    • 1st Edition
    • Peng Long + 1 more
    • English
    Deep Learning for Image Recognition provides a detailed explanation of the fundamental theories underpinning image recognition and code for recognition tasks in specific application scenarios. Readers can manipulate the existing code, thereby deepening their understanding. Chapters include project work enabling readers to apply the skills and knowledge gained from that section of the book. Projects are based on the accessible Pytorch framework, which is straightforward to learn and can be replicated and modified. Readers are presented with current research findings and up to date techniques in image recognition and deep learning.

  • Event-Driven State Estimation for Stochastic Networked Systems

    • 1st Edition
    • Cong Huang + 2 more
    • English
    Event-Driven State Estimation for Stochastic Networked Systems offers a comprehensive and clear explanation of recent developments in event-based state estimation for stochastic systems within limited communication networks, bringing together existing and emerging concepts. It provides a series of the latest results in, including but not limited to, recursive state estimation, fusion estimation, and state and fault estimation. The book provides practitioner readers with practical tools for the analysis and design of stochastic systems under limited communication networks, capturing recent advances in theory, technological aspects and real-world applications of advanced event-based state estimation methodologies. Realistic research problems are addressed in each chapter, with numerical and simulation results provided to reflect engineering practice, while demonstrating the main focus of the developed estimation approaches. The book is an advanced-level resource presented in an accessible manner, appealing to senior students as a core reference and to researchers and practitioners alike

  • Quantitative Human Physiology

    An Introduction
    • 3rd Edition
    • Joseph J Feher
    • English
    Quantitative Human Physiology: An Introduction, Third Edition, winner of a 2018 Textbook Excellence Award (Texty), is the first text to meet the needs of the undergraduate bioengineering student who is being exposed to physiology for the first time but requires a more analytical/quantitat... approach. This book explores how component behavior produces system behavior in physiological systems. Through text explanation, figures, and equations, it provides the engineering student with a basic understanding of physiological principles, with an emphasis on quantitative aspects. The third edition has been revised with more and expanded problem sets and improved illustrations.

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