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Among the wide range of programming tools available, the technical analysis and calculations are realized by MATLAB®, which is recognized as a convenient and effective tool for modern science and technology. Thus, mastering its latest versions and practical solutions is increasingly essential for the creation of new products in mechanics, electronics, chemistry, life sciences, and modern industry. Modern mechanical and tribology sciences specialists widely use computers and some special programs, but need a universal tool for solving, simulating, and modeling specific problems from their area. There is plenty of information available on MATLAB® for the general engineer, but there is a gap in the field for research that applies MATLAB® to two wide, interdisciplinary, and topical areas: tribology and mechanics. MATLAB® With Applications in Mechanics and Tribology explores how MATLAB® is used as a tool for subsequent computer solutions, applying it to both traditional and modern problems of mechanics and materials sciences. The problem solving in this book includes calculations of the mechanical parts, machine elements, production process, quality assurance, fluid mechanics parameters, thermodynamic and rheological properties of the materials as well as the state equations, descriptive statistics, and more. This book is ideal for scientists, students and professors of engineering courses, self-instructing readers, programmers, computer scientists, practitioners, and researchers looking for concise and clear information on learning and applying MATLAB® software to mechanics, tribology, and material physics.
Partial differential equations (PDEs) describe technological phenomena and processes used for the analysis, design, and modeling of technical products. Solutions of spatial and transient PDEs are realized by using the PDE Toolbox included in the MATLAB® software. MATLAB® is introduced here as an essential foundation for PDE, and the Modeler of the PDE Toolbox, with appropriate explanatory solutions, is applied to engineering problems in mechanics, heat/mass transfer, tribology, materials science, physics, and biotechnology. The appendixes contain collections of commands and functions used to solve actual engineering problems. FEATURES Includes the PDE Modeler interface with example solutions of two- and three-dimensional PDEs Presents methodologies for all types of PDEs as representative of any engineering problem Describes the ordinate differential equation (ODE) solver for initial value and boundary value problems (IVP and BVP) through practical examples from mechanics and the thermodynamic properties of materials Covers the basics of MATLAB® to solve both ODEs and PDEs Reviews spatially the one-dimensional PDE solver with actual engineering examples PDE Toolbox Primer for Engineering Applications with MATLAB® Basics is aimed at scientists, students, professionals, practitioners, self-taught readers, and researchers who need concise and clear information to study and apply MATLAB® software and the PDE Toolbox in engineering.
There is no doubt that there has been much excitement regarding the pioneering contributions of artificial intelligence (AI), the internet of things (IoT), and blockchain technologies and tools in visualizing and realizing smarter as well as sophisticated systems and services. However, researchers are being bombarded with various machine and deep learning algorithms, which are categorized as a part and parcel of the enigmatic AI discipline. The knowledge discovered gets disseminated to actuators and other concerned systems in order to empower them to intelligently plan and insightfully execute appropriate tasks with clarity and confidence. The IoT processes in conjunction with the AI algorithms and blockchain technology are bound to lay out a stimulating foundation for producing and sustaining smarter systems for society. Advancing Smarter and More Secure Industrial Applications Using AI, IoT, and Blockchain Technology articulates and accentuates various AI algorithms, fresh innovations in the IoT, and blockchain spaces. The domain of transforming raw data to information and to relevant knowledge is gaining prominence with the availability of data ingestion, processing, mining, analytics algorithms, platforms, frameworks, and other accelerators. Covering topics such as blockchain applications, Industry 4.0, and cryptography, this book serves as a comprehensive guide for AI researchers, faculty members, IT professionals, academicians, students, researchers, and industry professionals.
Big data generates around us constantly from daily business, custom use, engineering, and science activities. Sensory data is collected from the internet of things (IoT) and cyber-physical systems (CPS). Merely storing such a massive amount of data is meaningless, as the key point is to identify, locate, and extract valuable knowledge from big data to forecast and support services. Such extracted valuable knowledge is usually referred to as smart data. It is vital to providing suitable decisions in business, science, and engineering applications. Deep Learning Applications for Cyber-Physical Systems provides researchers a platform to present state-of-the-art innovations, research, and designs while implementing methodological and algorithmic solutions to data processing problems and designing and analyzing evolving trends in health informatics and computer-aided diagnosis in deep learning techniques in context with cyber physical systems. Covering topics such as smart medical systems, intrusion detection systems, and predictive analytics, this text is essential for computer scientists, engineers, practitioners, researchers, students, and academicians, especially those interested in the areas of internet of things, machine learning, deep learning, and cyber-physical systems.
Cyber-physical systems (CPS) can be defined as systems in which physical objects are represented in the digital world and integrated with computation, storage, and communication capabilities and are connected to each other in a network. The goal in the use of the CPS is integrating the dynamics of the physical processes with those of the software and networking, providing abstractions and modelling, design, and analysis techniques for the integrated whole. The notion of CPS is linked to concepts of robotics and sensor networks with intelligent systems proper of computational intelligence leading the pathway. Recent advances in science and engineering improve the link between computational and physical elements by means of intelligent systems, increasing the adaptability, autonomy, efficiency, functionality, reliability, safety, and usability of cyber-physical systems. The potential of cyber-physical systems will spread to several directions, including but not limited to intervention, precision manufacturing, operations in dangerous or inaccessible environments, coordination, efficiency, Maintenance 4.0, and augmentation of human capabilities. Design, Applications, and Maintenance of Cyber-Physical Systems gives insights about CPS as tools for integrating the dynamics of the physical processes with those of software and networking, providing abstractions and modelling, design, and analysis techniques for their smart manufacturing interoperation. The book will have an impact upon the research on robotics, mechatronics, integrated intelligent multibody systems, Industry 4.0, production systems management and maintenance, decision support systems, and Maintenance 4.0. The chapters discuss not only the technologies involved in CPS but also insights into how they are used in various industries. This book is ideal for engineers, practitioners, researchers, academicians, and students who are interested in a deeper understanding of cyber-physical systems (CPS), their design, application, and maintenance, with a special focus on modern technologies in Industry 4.0 and Maintenance 4.0.
With the field of computational statistics growing rapidly, there is a need for capturing the advances and assessing their impact. Advances in simulation and graphical analysis also add to the pace of the statistical analytics field. Computational statistics play a key role in financial applications, particularly risk management and derivative pricing, biological applications including bioinformatics and computational biology, and computer network security applications that touch the lives of people. With high impacting areas such as these, it becomes important to dig deeper into the subject and explore the key areas and their progress in the recent past. Methodologies and Applications of Computational Statistics for Machine Intelligence serves as a guide to the applications of new advances in computational statistics. This text holds an accumulation of the thoughts of multiple experts together, keeping the focus on core computational statistics that apply to all domains. Covering topics including artificial intelligence, deep learning, and trend analysis, this book is an ideal resource for statisticians, computer scientists, mathematicians, lecturers, tutors, researchers, academic and corporate libraries, practitioners, professionals, students, and academicians.
Tribology is related to friction, wear and lubrication of machine elements. Tribology not only deals with the design of fluid containment systems like seals and gasket but also with the lubrication of surfaces in relative motion. This book comprehensively discusses the theories and applications of hydrodynamic thrust bearing, gas (air) lubricated bearing and elasto-hydrodynamic lubrication. It elucidates the concepts related to friction, including coefficient of friction, friction instability and stick-slip motion. It clarifies the misconception that harder and cleaner surfaces produce better results in wear. Recent developments, including online condition monitoring (an integration of moisture sensor, wear debris and oil quality sensors) and multigrid technique, are discussed in detail. The book also offers design problems and their real-life applications for cams, followers, gears and bearings. MATLAB programs, frequently asked questions and multiple choice questions are interspersed throughout for easy understanding of the topics.
This book intend to supply readers with some MATLAB codes for ?nite element analysis of solids and structures. After a short introduction to MATLAB, the book illustrates the ?nite element implementation of some problems by simple scripts and functions. The following problems are discussed: • Discrete systems, such as springs and bars • Beams and frames in bending in 2D and 3D • Plane stress problems • Plates in bending • Free vibration of Timoshenko beams and Mindlin plates, including laminated composites • Buckling of Timoshenko beams and Mindlin plates The book does not intends to give a deep insight into the ?nite element details, just the basic equations so that the user can modify the codes. The book was prepared for undergraduate science and engineering students, although it may be useful for graduate students. TheMATLABcodesofthisbookareincludedinthedisk.Readersarewelcomed to use them freely. The author does not guarantee that the codes are error-free, although a major e?ort was taken to verify all of them. Users should use MATLAB 7.0 or greater when running these codes. Any suggestions or corrections are welcomed by an email to [email protected].
The purpose of this book is to introduce and study numerical methods basic and advanced ones for scientific computing. This last refers to the implementation of appropriate approaches to the treatment of a scientific problem arising from physics (meteorology, pollution, etc.) or of engineering (mechanics of structures, mechanics of fluids, treatment signal, etc.). Each chapter of this book recalls the essence of the different methods resolution and presents several applications in the field of engineering as well as programs developed under Matlab software.