Parallel Solution Methods In Computational Mechanics

This book follows the previously published title, Solving Large-scale Problems in Mechanics, edited by M. Papadrakakis. This first volume to be published in the Wiley Series in Solving Large-scale Problems in Mechanics is devoted to high-performance computing using the new generation of computers with parallel and distributed computing capabilities. Parallel and distributed processing is a rapidly growing area of high technology where engineering applications lagged behind hardware advances. New algorithms and codes are required in order to exploit effectively modern computer architectures, as programs suitable for conventional computers achieve very modest performances on these new machines. There is therefore an urgent need to develop and test powerful solution and data handling techniques capable of exploiting the potential of modern computers and of accomplishing the solution of complex engineering problems in an acceptable computing time. This volume intends capturing the latest developments in the field and to serve as an essential reference book on the subject. It comprises a comprehensive state-of-the-art treatment of theory and practice, illustrated by extensive numerical examples.

There is a need to solve problems in solid and fluid mechanics that currently exceed the resources of current and foreseeable supercomputers. The issue revolves around the number of degrees of freedom of simultaneous equations that one needs to accurately describe the problem, and the computer storage and speed limitations which prohibit such solutions. The goals of tHis symposium were to explore some of the latest work being done in both industry and academia to solve such extremely large problems, and to provide a forum for the discussion and prognostication of necessary future direc tions of both man and machine. As evidenced in this proceedings we believe these goals were met. Contained in this volume are discussions of: iterative solvers, and their application to a variety of problems, e.g. structures, fluid dynamics, and structural acoustics; iterative dynamic substructuring and its use in structural acoustics; the use of the boundary element method both alone and in conjunction with the finite element method; the application of finite difference methods to problems of incompressible, turbulent flow; and algorithms amenable to concurrent computations and their applications. Furthermore, discussions of existing computational shortcomings from the big picture point of view are presented that include recommendations for future work.

Introduces mechanical engineers to high-performance computing using the new generation of computers with vector and parallel processing capabilities that allow the solution to problems beyond the ken of traditional computers. The chapters present an introduction and overview, explain several methodo

In its third revised and extended edition the book offers an overview of the techniques used to solve problems in fluid mechanics on computers. The authors describe in detail the most often used techniques. Included are advanced techniques in computational fluid dynamics, such as direct and large-eddy simulation of turbulence. Moreover, a new section deals with grid quality and an extended description of discretization methods has also been included. Common roots and basic principles for many apparently different methods are explained. The book also contains a great deal of practical advice for code developers and users.

This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other machine learning method in computational mechanics. Part II highlights the applications of neural networks to a variety of problems of computational mechanics. The final chapter gives perspectives to the applications of the deep learning to computational mechanics.

Computational mechanics is a scientific discipline that marries physics, computers, and mathematics to emulate natural physical phenomena. It is a technology that allows scientists to study and predict the performance of various productsâ€"important for research and development in the industrialized world. This book describes current trends and future research directions in computational mechanics in areas where gaps exist in current knowledge and where major advances are crucial to continued technological developments in the United States.

This book explores the numerical algorithms underpinning modern finite element based computational mechanics software. It covers all the major numerical methods that are used in computational mechanics. It reviews the basic concepts in linear algebra and advanced matrix theory, before covering solution of systems of equations, symmetric eigenvalue solution methods, and direct integration of discrete dynamic equations of motion, illustrated with numerical examples. This book suits a graduate course in mechanics based disciplines, and will help software developers in computational mechanics. Increased understanding of the underlying numerical methods will also help practicing engineers to use the computational mechanics software more effectively.

Bringing together the world's leading researchers and practitioners of computational mechanics, these new volumes meet and build on the eight key challenges for research and development in computational mechanics. Researchers have recently identified eight critical research tasks facing the field of computational mechanics. These tasks have come about because it appears possible to reach a new level of mathematical modelling and numerical solution that will lead to a much deeper understanding of nature and to great improvements in engineering design. The eight tasks are: The automatic solution of mathematical models Effective numerical schemes for fluid flows The development of an effective mesh-free numerical solution method The development of numerical procedures for multiphysics problems The development of numerical procedures for multiscale problems The modelling of uncertainties The analysis of complete life cycles of systems Education - teaching sound engineering and scientific judgement Readers of Computational Fluid and Solid Mechanics 2003 will be able to apply the combined experience of many of the world's leading researchers to their own research needs. Those in academic environments will gain a better insight into the needs and constraints of the industries they are involved with; those in industry will gain a competitive advantage by gaining insight into the cutting edge research being carried out by colleagues in academia. Features Bridges the gap between academic researchers and practitioners in industry Outlines the eight main challenges facing Research and Design in Computational mechanics and offers new insights into the shifting the research agenda Provides a vision of how strong, basic and exciting education at university can be harmonized with life-long learning to obtain maximum value from the new powerful tools of analysis