Modern machine design challenges engineers with a myriad of nonlinear problems, among them fatigue, friction, plasticity, and excessive deformation. Today's advanced numerical computer programs bring optimal solutions to these complex problems within reach, but not without a trained and experienced overseer. Nonlinear Problems in Machine Des
Modern machine design challenges engineers with a myriad of nonlinear problems, among them fatigue, friction, plasticity, and excessive deformation. Today's advanced numerical computer programs bring optimal solutions to these complex problems within reach, but not without a trained and experienced overseer. Nonlinear Problems in Machine Design provides that training and experience. It acquaints readers with the modern analytical methods of machine design and enables them to use those methods in daily applications. The authors first build the theoretical foundation, then focus on the application of the finite element method to machine design problems. They offer practical examples with solutions generated using both the ANSYS and MSC.NASTRAN finite element programs, demonstrating the reliability of the results, offering readers experience with the two most widely used programs in industry. Developed through the authors' extensive knowledge of engineering theory and their experience in verifying the accuracy and applicability of computer generated solutions, this book helps ensure foolproof results when designing machine parts. Nonlinear Problems in Machine Design is unique in its focus, will prove equally valuable to students and practitioners, and appears destined to become a standard in its field.
Computer aided design (CAD) emerged in the 1960s out of the growing acceptance of the use of the computer as a design tool for complex systems. As computers have become faster and less expensive while handling an increasing amount of information, their use in machine design has spread from large industrial needs to the small designer.
The book consists of 31 chapters in which the authors deal with multiple aspects of modeling, utilization and implementation of semantic methods for knowledge management and communication in the context of human centered computing. It is assumed that the modern human centered computing requires the intensive application of these methods as well as effective integration with multiple techniques of computational collective intelligence. The book is organized in four parts devoted to the presentation of utilization of knowledge processing in agent and multiagent systems, application of computational collective intelligence to knowledge management, models for collectives of intelligent agents, and models and environments tailored directly to human-centered computing. All chapters in the book discuss theoretical and practical issues related to various models and aspects of computational techniques for semantic methods, which are currently studied and developed in many academic and industry centers over the world. The editors hope that the book can be useful for graduate and PhD students of computer science, as well as for mature academics, researchers and practitioners interested in developing of modern methods for representation, processing and distribution of knowledge in the context of human centered computing and by means of computer based information systems. It is the hope of the editors that readers of this volume can find in all chosen chapters many inspiring ideas and influential practical examples, as well as use them in their current and future work.
Based on course-tested material, this rigorous yet accessible graduate textbook covers both fundamental and advanced optimization theory and algorithms. It covers a wide range of numerical methods and topics, including both gradient-based and gradient-free algorithms, multidisciplinary design optimization, and uncertainty, with instruction on how to determine which algorithm should be used for a given application. It also provides an overview of models and how to prepare them for use with numerical optimization, including derivative computation. Over 400 high-quality visualizations and numerous examples facilitate understanding of the theory, and practical tips address common issues encountered in practical engineering design optimization and how to address them. Numerous end-of-chapter homework problems, progressing in difficulty, help put knowledge into practice. Accompanied online by a solutions manual for instructors and source code for problems, this is ideal for a one- or two-semester graduate course on optimization in aerospace, civil, mechanical, electrical, and chemical engineering departments.
Today, switched reluctance machines (SRMs) play an increasingly important role in various sectors due to advantages such as robustness, simplicity of construction, low cost, insensitivity to high temperatures, and high fault tolerance. They are frequently used in fields such as aeronautics, electric and hybrid vehicles, and wind power generation. This book is a comprehensive resource on the design, modeling, and control of SRMs with methods that demonstrate their good performance as motors and generators.
Introduction to Advanced Soft Robotics is an introductory textbook on soft body robotics. The content is designed to enable readers to better understand soft body robotics. Starting with an introduction to the subject, contents explain fundamental concepts such as perception and sensing, fabrication techniques and material design. These introductory chapters demonstrate the design concept and related design structures of soft robots from multiple perspectives, which can provide considerable design references for robotics learners and enthusiasts. Next, the book explains modeling and control for soft robotics and the applications. Key features of this book include easy-to-understand language and format, simple illustrations and a balanced overview of the subject (including a section on challenges and future prospects for soft robotics), and scientific references.