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Data science for engineers
\"With tremendous improvement in computational power and availability of rich data, almost all engineering disciplines use data science at some level. This textbook presents material on data science comprehensively, and in a structured manner. It provides conceptual understanding of the fields of data science, machine learning, and artificial intelligence, with enough level of mathematical details necessary for the readers. This will help readers understand major thematic ideas in data science, machine learning and artificial intelligence, and implement first-level data science solutions to practical engineering problems. The book- Provides a systematic approach for understanding data science techniques Explain why machine learning techniques are able to cross-cut several disciplines. Covers topics including statistics, linear algebra and optimization from a data science perspective. Provides multiple examples to explain the underlying ideas in machine learning algorithms Describes several contemporary machine learning algorithms The textbook is primarily written for undergraduate and senior undergraduate students in different engineering disciplines including chemical engineering, mechanical engineering, electrical engineering, electronics and communications engineering for courses on data science, machine learning and artificial intelligence.\"--Page 4 of cover.
BOOK
Petroleum Production Engineering - A Computer-Assisted Approach
This book provides handy guidelines to designing, analyzing and optimizing petroleum production systems. Broken into four parts, this book covers the full scope of petroleum production engineering, featuring stepwise calculations and computer-based spreadsheet programs. Part one contains discussions of petroleum production engineering fundamentals, empirical models for production decline analysis, and the performance of oil and natural gas wells. Part two presents principles of designing and selecting the main components of petroleum production systems including: well tubing, separation and dehydration systems, liquid pumps, gas compressors, and pipelines for oil and gas transportation. Part three introduces artificial lift methods, including sucker rod pumping systems, gas lift technology, electrical submersible pumps and other artificial lift systems. Part four is comprised of production enhancement techniques including, identifying well problems, designing acidizing jobs, guidelines to hydraulic fracturing and job evaluation techniques, and production optimization techniques.
eBook
Engineering Applications
ENGINEERING APPLICATIONS A comprehensive text on the fundamental principles of mechanical engineering Engineering Applications presents the fundamental principles and applications of the statics and mechanics of materials in complex mechanical systems design. Using MATLAB to help solve problems with numerical and analytical calculations, authors and noted experts on the topic Mihai Dupac and Dan B. Marghitu offer an understanding of the static behaviour of engineering structures and components while considering the mechanics of materials knowledge as the most important part of their design. The authors explore the concepts, derivations, and interpretations of general principles and discuss the creation of mathematical models and the formulation of mathematical equations. This practical text also highlights the solutions of problems solved analytically and numerically using MATLAB. The figures generated with MATLAB reinforce visual learning for students and professionals as they study the programs. This important text:Shows how mechanical principles are applied to engineering designCovers basic material with both mathematical and physical insightProvides an understanding of classical mechanical principlesOffers problem solutions using MATLABReinforces learning using visual and computational techniques Written for students and professional mechanical engineers, Engineering Applications helpshone reasoning skills in order to interpret data and generate mathematical equations, offering different methods of solving them for evaluating and designing engineering systems.
eBook
Engineering design : representation and reasoning
\"This text demonstrates that symbolic representation, and related problem-solving methods, offer significant opportunities to clarify and articulate concepts of design\"--Provided by publisher.
Book
Data analysis and statistics for geography, environmental science, and engineering
This practical, classroom-tested textbook helps readers learn quantitative methodology, including how to implement advanced analysis methods using an open-source software platform. Based on the author's many years of teaching undergraduate and graduate students in several countries, the book brings together principles of statistics and probability, multivariate analysis, and spatial analysis methods applied to a variety of geographical and environmental models. Theory is accompanied by practical hands-on computer exercises, progressing from easy to difficult. The text also presents a review of mathematical methods, making the book self-contained.
eBook
Kinematic Control of Redundant Robot Arms Using Neural Networks
<b>Presents pioneering and comprehensive work on engaging movement in robotic arms, with a specific focus on neural networks</b> <p>This book presents and investigates different methods and schemes for the control of robotic arms whilst exploring the field from all angles. On a more specific level, it deals with the dynamic-neural-network based kinematic control of redundant robot arms by using theoretical tools and simulations. <p><i>Kinematic Control of Redundant Robot Arms Using Neural Networks</i> is divided into three parts: Neural Networks for Serial Robot Arm Control; Neural Networks for Parallel Robot Control; and Neural Networks for Cooperative Control. The book starts by covering zeroing neural networks for control, and follows up with chapters on adaptive dynamic programming neural networks for control; projection neural networks for robot arm control; and neural learning and control co-design for robot arm control. Next, it looks at robust neural controller design for robot arm control and teaches readers how to use neural networks to avoid robot singularity. It then instructs on neural network based Stewart platform control and neural network based learning and control co-design for Stewart platform control. The book finishes with a section on zeroing neural networks for robot arm motion generation. <ul> <li>Provides comprehensive understanding on robot arm control aided with neural networks</li> <li>Presents neural network-based control techniques for single robot arms, parallel robot arms (Stewart platforms), and cooperative robot arms</li> <li>Provides a comparison of using neural networks for control purposes rather than traditional control based methods</li> <li>Includes simulation and modelling tasks (e.g., MATLAB) for onward application for research and engineering development</li> </ul> <p>By focusing on robot arm control aided by neural networks whilst examining central topics surrounding the field, <i>Kinematic Control of Redundant Robot Arms Using Neural Networks</i> is an excellent book for graduate students and academic and industrial researchers studying neural dynamics, neural networks, analog and digital circuits, mechatronics, and mechanical engineering.
eBook
Data-driven science and engineering : machine learning, dynamical systems, and control
\"Data-driven discovery is revolutionizing the modelling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modelling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Aimed at advanced undergraduate and beginning graduate students in the engineering and physical sciences, the text presents a range of topics and methods from introductory to state of the art\"-- Provided by publisher.
Book
Modeling and simulation support for system of systems engineering applications
“...a much-needed handbook with contributions from well-chosen practitioners. A primary accomplishment is to provide guidance for those involved in modeling and simulation in support of Systems of Systems development, more particularly guidance that draws on well-conceived academic research to define concepts and terms, that identifies primary challenges for developers, and that suggests fruitful approaches grounded in theory and successful examples.” Paul Davis, The RAND Corporation
Modeling and Simulation Support for System of Systems Engineering Applications provides a comprehensive overview of the underlying theory, methods, and solutions in modeling and simulation support for system of systems engineering. Highlighting plentiful multidisciplinary applications of modeling and simulation, the book uniquely addresses the criteria and challenges found within the field. Beginning with a foundation of concepts, terms, and categories, a theoretical and generalized approach to system of systems engineering is introduced, and real-world applications via case studies and examples are presented. A unified approach is maintained in an effort to understand the complexity of a single system as well as the context among other proximate systems. In addition, the book features:
Cutting edge coverage of modeling and simulation within the field of system of systems, including transportation, system health management, space mission analysis, systems engineering methodology, and energy State-of-the-art advances within multiple domains to instantiate theoretic insights, applicable methods, and lessons learned from real-world applications of modeling and simulation The challenges of system of systems engineering using a systematic and holistic approach Key concepts, terms, and activities to provide a comprehensive, unified, and concise representation of the field A collection of chapters written by over 40 recognized international experts from academia, government, and industry A research agenda derived from the contribution of experts that guides scholars and researchers towards open questions Modeling and Simulation Support for System of Systems Engineering Applications is an ideal reference and resource for academics and practitioners in operations research, engineering, statistics, mathematics, modeling and simulation, and computer science. The book is also an excellent course book for graduate and PhD-level courses in modeling and simulation, engineering, and computer science.
eBook