Computational Dynamics

A practical approach to the computational methods used to solve real-world dynamics problems Computational dynamics has grown rapidly in recent years with the advent of high-speed digital computers and the need to develop simulation and analysis computational capabilities for mechanical and aerospace systems that consist of interconnected bodies. Computational Dynamics, Second Edition offers a full introduction to the concepts, definitions, and techniques used in multibody dynamics and presents essential topics concerning kinematics and dynamics of motion in two and three dimensions. Skillfully organized into eight chapters that mirror the standard learning sequence of computational dynamics courses, this Second Edition begins with a discussion of classical techniques that review some of the fundamental concepts and formulations in the general field of dynamics. Next, it builds on these concepts in order to demonstrate the use of the methods as the foundation for the study of computational dynamics. Finally, the book presents different computational methodologies used in the computer-aided analysis of mechanical and aerospace systems. Each chapter features simple examples that show the main ideas and procedures, as well as straightforward problem sets that facilitate learning and help readers build problem-solving skills. Clearly written and ready to apply, Computational Dynamics, Second Edition is a valuable reference for both aspiring and practicing mechanical and aerospace engineers.

This book serves as a complete and self-contained introduction to the principles of Computational Fluid Dynamic (CFD) analysis. It is deliberately short (at approximately 300 pages) and can be used as a text for the first part of the course of applied CFD followed by a software tutorial. The main objectives of this non-traditional format are: 1) To introduce and explain, using simple examples where possible, the principles and methods of CFD analysis and to demystify the `black box’ of a CFD software tool, and 2) To provide a basic understanding of how CFD problems are set and which factors affect the success and failure of the analysis. Included in the text are the mathematical and physical foundations of CFD, formulation of CFD problems, basic principles of numerical approximation (grids, consistency, convergence, stability, and order of approximation, etc), methods of discretization with focus on finite difference and finite volume techniques, methods of solution of transient and steady state problems, commonly used numerical methods for heat transfer and fluid flows, plus a brief introduction into turbulence modeling.

Computational fluid dynamics (CFD) is concerned with the efficient numerical solution of the partial differential equations that describe fluid dynamics. CFD techniques are commonly used in the many areas of engineering where fluid behavior is an important factor. Traditional fields of application include aerospace and automotive design, and more recently, bioengineering and consumer and medical electronics. With Applied Computational Fluid Dynamics Techniques, 2nd edition, Rainald L?hner introduces the reader to the techniques required to achieve efficient CFD solvers, forming a bridge between basic theoretical and algorithmic aspects of the finite element method and its use in an industrial context where methods have to be both as simple but also as robust as possible. This heavily revised second edition takes a practice-oriented approach with a strong emphasis on efficiency, and offers important new and updated material on; Overlapping and embedded grid methods Treatment of free surfaces Grid generation Optimal use of supercomputing hardware Optimal shape and process design Applied Computational Fluid Dynamics Techniques, 2nd edition is a vital resource for engineers, researchers and designers working on CFD, aero and hydrodynamics simulations and bioengineering. Its unique practical approach will also appeal to graduate students of fluid mechanics and aero and hydrodynamics as well as biofluidics.

A unified and coherent treatment of analytical, computational and experimental techniques of nonlinear dynamics with numerous illustrative applications. Features a discourse on geometric concepts such as Poincare maps. Discusses chaos, stability and bifurcation analysis for systems of differential and algebraic equations. Includes scores of examples to facilitate understanding.

Computational methods for the modeling and simulation of the dynamic response and behavior of particles, materials and structural systems have had a profound influence on science, engineering and technology. Complex science and engineering applications dealing with complicated structural geometries and materials that would be very difficult to treat using analytical methods have been successfully simulated using computational tools. With the incorporation of quantum, molecular and biological mechanics into new models, these methods are poised to play an even bigger role in the future. Advances in Computational Dynamics of Particles, Materials and Structures not only presents emerging trends and cutting edge state-of-the-art tools in a contemporary setting, but also provides a unique blend of classical and new and innovative theoretical and computational aspects covering both particle dynamics, and flexible continuum structural dynamics applications. It provides a unified viewpoint and encompasses the classical Newtonian, Lagrangian, and Hamiltonian mechanics frameworks as well as new and alternative contemporary approaches and their equivalences in [start italics]vector and scalar formalisms[end italics] to address the various problems in engineering sciences and physics. Highlights and key features Provides practical applications, from a unified perspective, to both particle and continuum mechanics of flexible structures and materials Presents new and traditional developments, as well as alternate perspectives, for space and time discretization Describes a unified viewpoint under the umbrella of Algorithms by Design for the class of linear multi-step methods Includes fundamentals underlying the theoretical aspects and numerical developments, illustrative applications and practice exercises The completeness and breadth and depth of coverage makes Advances in Computational Dynamics of Particles, Materials and Structures a valuable textbook and reference for graduate students, researchers and engineers/scientists working in the field of computational mechanics; and in the general areas of computational sciences and engineering.

Design Optimization of Fluid Machinery: Applying Computational Fluid Dynamics and Numerical Optimization Drawing on extensive research and experience, this timely reference brings together numerical optimization methods for fluid machinery and its key industrial applications. It logically lays out the context required to understand computational fluid dynamics by introducing the basics of fluid mechanics, fluid machines and their components. Readers are then introduced to single and multi-objective optimization methods, automated optimization, surrogate models, and evolutionary algorithms. Finally, design approaches and applications in the areas of pumps, turbines, compressors, and other fluid machinery systems are clearly explained, with special emphasis on renewable energy systems. Written by an international team of leading experts in the field Brings together optimization methods using computational fluid dynamics for fluid machinery in one handy reference Features industrially important applications, with key sections on renewable energy systems Design Optimization of Fluid Machinery is an essential guide for graduate students, researchers, engineers working in fluid machinery and its optimization methods. It is a comprehensive reference text for advanced students in mechanical engineering and related fields of fluid dynamics and aerospace engineering.

A practical, easily accessible guide for bench-top chemists, this book focuses on accurately applying computational chemistry techniques to everyday chemistry problems. Provides nonmathematical explanations of advanced topics in computational chemistry. Focuses on when and how to apply different computational techniques. Addresses computational chemistry connections to biochemical systems and polymers. Provides a prioritized list of methods for attacking difficult computational chemistry problems, and compares advantages and disadvantages of various approximation techniques. Describes how the choice of methods of software affects requirements for computer memory and processing time.

COMPUTATIONAL GEOMECHANICS The new edition of the first book to cover the computational dynamic aspects of geomechanics, now including more practical applications and up-to-date coverage of current research in the field[/b] Advances in computational geomechanics have dramatically improved understanding of the behavior of soils and the ability of engineers to design increasingly sophisticated constructions in the ground. When Professor Olek Zienkiewicz began the application of numerical approaches to solid dynamics at Swansea University, it became evident that realistic prediction of the behavior of soil masses could only be achieved if the total stress approaches were abandoned. Computational Geomechanics introduces the theory and application of Zienkiewicz’s computational approaches that remain the basis for work in the area of saturated and unsaturated soil to this day. Written by past students and colleagues of Professor Zienkiewicz, this extended Second Edition provides formulations for a broader range of problems, including failure load under static loading, saturated and unsaturated consolidation, hydraulic fracturing, and liquefaction of soil under earthquake loading. The internationally-recognized team of authors incorporates current computer technologies and new developments in the field, particularly in the area of partial saturation, as they guide readers on how to properly apply the formulation in their work. This one-of-a-kind volume: Explains the Biot-Zienkiewicz formulation for saturated and unsaturated soil Covers multiple applications to static and dynamic problems for saturated and unsaturated soil in areas such as earthquake engineering and fracturing of soils and rocks Features a completely new chapter on fast catastrophic landslides using depth integrated equations and smoothed particle hydrodynamics with applications Presents the theory of porous media in the saturated and unsaturated states to establish the foundation of the problem of soil mechanics Provides a quantitative description of soil behavior including simple plasticity models, generalized plasticity, and critical state soil mechanics Includes numerous questions, problems, hands-on experiments, applications to other situations, and example code for GeHoMadrid Computational Geomechanics: Theory and Applications, Second Edition is an ideal textbook for specialist and general geotechnical postgraduate courses, and a must-have reference for researchers in geomechanics and geotechnical engineering, for software developers and users of geotechnical finite element software, and for geotechnical analysts and engineers making use of the numerical results obtained from the Biot-Zienkiewicz formulation.

Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence. Computational intelligence schemes are investigated with the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples. Key features: Covers all the aspects of fuzzy, neural and evolutionary approaches with worked out examples, MATLAB® exercises and applications in each chapter Presents the synergies of technologies of computational intelligence such as evolutionary fuzzy neural fuzzy and evolutionary neural systems Considers real world problems in the domain of systems modelling, control and optimization Contains a foreword written by Lotfi Zadeh Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing is an ideal text for final year undergraduate, postgraduate and research students in electrical, control, computer, industrial and manufacturing engineering.

Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments. The main focus of this text is centred on the computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. Engelbrecht provides readers with a wide knowledge of Computational Intelligence (CI) paradigms and algorithms; inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without any difficulty through a single Java class as part of the CI library. Key features of this second edition include: A tutorial, hands-on based presentation of the material. State-of-the-art coverage of the most recent developments in computational intelligence with more elaborate discussions on intelligence and artificial intelligence (AI). New discussion of Darwinian evolution versus Lamarckian evolution, also including swarm robotics, hybrid systems and artificial immune systems. A section on how to perform empirical studies; topics including statistical analysis of stochastic algorithms, and an open source library of CI algorithms. Tables, illustrations, graphs, examples, assignments, Java code implementing the algorithms, and a complete CI implementation and experimental framework. Computational Intelligence: An Introduction, Second Edition is essential reading for third and fourth year undergraduate and postgraduate students studying CI. The first edition has been prescribed by a number of overseas universities and is thus a valuable teaching tool. In addition, it will also be a useful resource for researchers in Computational Intelligence and Artificial Intelligence, as well as engineers, statisticians, operational researchers, and bioinformaticians with an interest in applying AI or CI to solve problems in their domains. Check out http://www.ci.cs.up.ac.za for examples, assignments and Java code implementing the algorithms.