Books in Physical sciences and engineering

Optics and Photonics

1st Edition
January 1, 2026
Andrew Zhou
English

Optics and Photonics is a valuable and easy-to-read text on both the fundamentals and applications, including sections on geometrical optics, wave optics, photonics and lasers, optical materials, and real-world photonics applications. Emerging trends and future directions are also discussed. A structured progression is adopted, starting with basic concepts, and building up to more advanced topics involving components and systems. This book also keeps a balance between depth and breadth for such a diversified and large field. This framework is designed to meet the needs of undergraduate and graduate students, while also providing technicians and researchers with a deeper understanding of the principles and application relevant to their work. The solutions to multiple choice reading questions, end of chapter problems and projects are provided for instructors, as well as the PowerPoint presentations, a test bank and a separate lab manual, reinforcing understanding and application.

Digital Twins of Advanced Materials Processing

1st Edition
January 1, 2026
Tarasankar DebRoy + 1 more
English
Paperback
9 7 8 0 4 4 3 3 2 9 1 8 0
eBook
9 7 8 0 4 4 3 3 2 9 1 9 7

Digital twins represent an emerging technology of immense potential across various industries. Their significance is particularly pronounced within Industry 4.0 and smart manufacturing paradigms, which strive to elevate efficiency and quality through seamless digital integration. By amassing and scrutinizing extensive data streams, digital twins empower data-centric decision-making—a pivotal asset in contemporary industry. Digital Twins of Advanced Materials Processing bridges the gap in comprehensive resources concerning advanced materials processing, a domain characterized by rapid evolution. It provides pragmatic remedies and real-world case studies, catering to tangible implementation needs. Moreover, digital twins hold the capacity to amplify efficiency and innovation within materials processing—a perspective deeply explored within this book, rendering it invaluable for professionals, researchers, and students alike. The prospects of employing digital twins in materials processing span diverse horizons: refining materials innovation, streamlining processes, enabling data-driven maintenance, enhancing product quality, and unearthing insights rooted in data. The book also undertakes the challenge of addressing key issues encompassing data amalgamation and integrity, model validation and calibration, software and data safeguarding, scalability, and cost considerations.

Monitoring and Control Techniques in Metal Additive Manufacturing

1st Edition
January 1, 2026
Ibrahim Tansel
English

Monitoring and Control Techniques in Metal Additive Manufacturing provides an overview of monitoring methods in metal additive manufacturing, demonstrating the use of manufacturing parameter control for quality improvement based on simulations and measurements. The implementation of structural health monitoring (SHM) methods to evaluate the quality of manufactured parts and detect defects is included. The book starts with chapters introducing metal additive manufacturing, discussing the benefits of integrating monitoring methods into the additive manufacturing process and the benefits of control mechanisms. The following chapter outlines various monitoring methods, including thermal sensors, vision sensors, non-destructive testing (including ultrasound, acoustic emission sensors, and radiography), and optical emission spectroscopy. From there, computational methods for the analysis of data and decision making are discussed, including statistical methods, machine learning techniques, and deep convolutional neural network approaches used for process visualization, analysis, and classification. Numerical methods used to estimate temperature, strain distribution, and cavity percentages are also covered, as are structural health monitoring methods. The book also features a chapter dedicated to real-world applications of these techniques, and concludes with a chapter evaluating the performance of the previously discussed methods as well as a look at future trends.

Multilevel Quantum Metaheuristics

1st Edition
January 1, 2026
Siddhartha Bhattacharyya + 4 more
English

Multilevel Quantum Metaheuristics: Applications in Data Exploration explores the most recent advances in hybrid quantum-inspired algorithms. Combining principles of quantum mechanics with metaheuristic techniques for efficient data optimization, this book examines multilevel quantum systems characterized by qudits and higher-level quantum states as more robust alternatives to conventional bilevel quantum approaches. It introduces novel multilevel applications of quantum metaheuristics for addressing optimization problems in areas including function optimization, data analysis, scheduling, and signal processing. The book also showcases real-world examples, case studies, and contributions that emphasize the effectiveness of proposed multilevel techniques over existing bilevel methods. Researchers, professionals, and engineers working on intelligent computing, quantum computing, data processing, clustering, and analysis, and those interested in the synergies between quantum computing, metaheuristics, and multilevel quantum systems for enhanced data exploration and analysis will find this book to be of great value.

Functional Analysis: Theory and Applications

1st Edition
January 1, 2026
Ravi P. Agarwal + 2 more
English

An applied understanding of functional analysis is essential for students pursuing research or careers in pure mathematics, applied mathematics, mathematical physics, and engineering, among other disciplines.Function... Analysis: Theory and Applications offers a comprehensive exploration of functional analysis. Authored by esteemed mathematicians with extensive expertise in the field, this book thoroughly introduces fundamental concepts in functional analysis, including Banach spaces, Hilbert spaces, operator theory, nonlinear analysis, linear operators, and normed spaces, and implements these in real-world problems across various scientific and engineering disciplines.The book's rigorous mathematical treatment is combined with worked examples, exercises and solutions, visual aids, application case studies, and future directions across all chapters to reinforce learning, while appendices offer supplementary materials, proofs of theorems, and tables of important results, among other resources.

Autonomous Vehicle Safety Solutions

1st Edition
January 1, 2026
Aparna Kumari
English

Autonomous Vehicle Safety Solutions: Foundations, Technologies, and Prospects for the Future addresses the dynamically evolving state of the art that traverses and brings together automotive engineering, electronics engineering, and computer science. Its technical overview of smart vehicles' capabilities, propelled by headway in artificial intelligence and sensor technologies, enables in-depth understanding of the safety-assurance complexities that guide their design and operation.The comprehensive volume distinguishes itself for its treatment of several exciting, emerging opportunities and trends, including machine learning algorithms, V2X connectivity, and cybersecurity. Up-to-date applications are featured through practical examples and expert insights, bringing additional value to a discourse which underscores the critical need for ongoing safety advancements and adaptability in the fast-moving context of autonomous driving systems, with their related implications on sustainability and society as a whole.The outcome is a cornerstone resource for academia and industry alike that encourages further transformative, interdisciplinary investigations to bring safety solutions to maturity and subsequent rigorous testing for validation standards to be defined, thus realizing, in a future not distant from now, a scenario where self-driving vehicles can co-exist seamlessly with traditional modes of transportation and also integrate reliably, efficiently, and without risks within the larger infrastructure.

Challenges and Applications of Generative Large Language Models

1st Edition
January 1, 2026
Anitha S. Pillai + 2 more
English

Large Language Models (LLMs) are a form of generative AI, based on Deep Learning, that rely on very large textual datasets, and are composed of hundreds of millions (or even billions) of parameters. LLMs can be trained and then refined to perform several NLP tasks like generation of text, summarization, translation, prediction, and more. Challenges and Applications of Generative Large Language Models assists readers in understanding LLMs, their applications in various sectors, challenges that need to be encountered while developing them, open issues, and ethical concerns. LLMs are just one approach in the huge set of methodologies provided by AI. The book, describing strengths and weaknesses of such models, enables researchers and software developers to decide whether an LLM is the right choice for the problem they are trying to solve. AI is the new buzzword, in particular Generative AI for human language (LLMs). As such, an overwhelming amount of hype is obfuscating and giving a distorted view about AI in general, and LLMs in particular. Thus, trying to provide an objective description of LLMs is useful to any person (researcher, professional, student) who is starting to work with human language. The risk, otherwise, is to forget the whole set of methodologies developed by AI in the last decades, sticking with only one model which, although very powerful, has known weaknesses and risks. Given the high level of hype around such models, Challenges and Applications of Generative Large Language Models (LLMs) enables readers to clarify and understand their scope and limitations.

Engineering Materials for 3D Printing

1st Edition
January 1, 2026
Rupinder Singh + 3 more
English

3D printing processes have promising advantages over conventional manufacturing processes from a functional ability viewpoint. In the past 30 years, a variety of additive manufacturing-based 3D printing processes have been reported for the fabrication of functional prototypes, using materials such as thermoplastic, resins, metal and their alloys. While there is a significant amount of information on various 3D printing processes, and materials that may be used in 3D printing-based manufacturing practices for engineering applications, there is far less information on 3D printable materials for structural and non-structural engineering applications. Engineering Materials for 3D Printing fills this gap. The book includes three sections and provides an insight on the development and characterization of polymer-based 3D printed materials by different processes such as extrusion, sol-gel, and pulverization along with meta-structure properties for various structural applications

Decision Systems

1st Edition
January 1, 2026
Pallavi Vijay Chavan + 3 more
English

Decision Systems: Integrating Machine Learning, Fuzzy Logic, and Artificial Neural Networks provides readers with a comprehensive understanding of the principal techniques used to build effective decision-making systems. This book covers the fundamental principles and concepts of machine learning, fuzzy logic, and artificial neural networks, and explains how these techniques can be used to build intelligent decision-making systems that can learn from data, reason, and make accurate predictions. The book also presents a wide range of applications of machine learning, fuzzy logic, and artificial neural networks in various domains, such as engineering, medicine, finance, and robotics. The book also provides practical guidance on how to design and implement effective decision-making systems using these techniques and discusses the potential challenges and limitations of machine learning, fuzzy logic, and artificial neural networks, and how to overcome them. The book provides a stepwise approach to provide readers with the knowledge and tools they need to build intelligent decision-making systems, including a robust introduction to the mathematical concepts and principles necessary to understand the concepts and applications of Decision Systems and Machine Learning algorithms. Next, the book provides readers with an in-depth explanation and demonstration of two of the major machine learning techniques – Fuzzy Logic/Fuzzy Set Theory and Artificial Neural Networks – followed by an in-depth look at more advanced topics that play essential roles in making machine learning algorithms more useful in practice, including creating full-fledged Recurrent Networks and their mathematical foundations, Associative Memories, and Deep Learning networks such as Convolutional Neural Networks, Generative Adversarial Networks, Radial Basis Function Networks, Multilayer Perceptrons, and Self-Organizing Maps. The lynchpin of the book provides readers with an understanding of how the various types of techniques can be integrated to create dynamic Decision Systems. The book wraps up with coverage of challenges and opportunities in Decision Systems along with real-world applications of Decision Systems with case studies in healthcare, finance, education, social media, and agriculture.

Floating Photovoltaics

1st Edition
January 1, 2026
Anik Goswami + 3 more
English

Floating Photovoltaics: Design, Performance, Degradation, Financial Sustainability, and Environmental Impacts offers broad coverage of floating photovoltaic (FPV) systems, enabling the reader to understand design, deployment, and performance, as we all economic feasibility and environmental factors. The book introduces a range of pre-feasibility analysis methods such as location selection, bathymetric studies, design of anchors and mooring, effect of waves, and tilt angle. Design criteria of FPV systems are then discussed in detail, from module selection and inverter selection to conditions and operating temperature. The types of degradation and the effect of degradation on long-term performance of FPV systems are analyzed, with a parameter level study helping to determine the exact long-term degradation of FPV systems, as well as the effect of maintenance on performance of FPV systems. The final chapters in the book focus on financial sustainability, environmental impacts, and policy recommendations, supporting further development, deployment, and decision-making with regard to FPV technology and projects. Researchers, advanced students, faculty, engineers, R&D, scientists, and policy makers with an interest in floating photovoltaic systems will find this book to be an interesting resource.

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