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Fundamentals of Engineering Numerical Analysis - Softcover

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9780521711234: Fundamentals of Engineering Numerical Analysis

Synopsis

Since the original publication of this book, available computer power has increased greatly. Today, scientific computing is playing an ever more prominent role as a tool in scientific discovery and engineering analysis. In this second edition, the key addition is an introduction to the finite element method. This is a widely used technique for solving partial differential equations (PDEs) in complex domains. This text introduces numerical methods and shows how to develop, analyze, and use them. Complete MATLAB programs for all the worked examples are now available at www.cambridge.org/Moin, and more than 30 exercises have been added. This thorough and practical book is intended as a first course in numerical analysis, primarily for new graduate students in engineering and physical science. Along with mastering the fundamentals of numerical methods, students will learn to write their own computer programs using standard numerical methods.

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About the Author

Parviz Moin is the Franklin P. and Caroline M. Johnson Professor of Mechanical Engineering at Stanford University. He received his bachelor's degree in mechanical engineering from the University of Minnesota in 1974 and his master's and PhD degrees in mathematics and mechanical engineering from Stanford in 1978. He held the posts of National Research Council Fellow, Staff Scientist, and Senior Staff Scientist at NASA Ames Research Center. He joined the Stanford faculty in September 1986. He founded the Center for Turbulence Research and the Stanford Institute for Computational and Mathematical Engineering. Currently he is Director of the Center for Turbulence Research and the Department of Energy's Predictive Science Academic Alliance Program at Stanford. He is actively involved in the editorial boards of the Annual Review of Fluid Mechanics, the Journal of Computational Physics, the Physics of Fluids, SIAM Journal of Multi-Scale Modeling and Simulation and the Journal of Flow Turbulence and Combustion. Professor Moin pioneered the use of high fidelity numerical simulations and massively parallel computers for the study of turbulence physics. His distinctions include NASA's Exceptional Scientific Achievement and Outstanding Leadership Medals, the Einstein Professorship of the Chinese Academy of Sciences, the Lawrence Sperry Award of the American Institute of Aeronautics and Astronautics (AIAA), the Fluid Dynamics Prize of the American Physical Society and the Fluid Dynamics Award of AIAA. Professor Moin is a Fellow of the American Physical Society and AIAA. He is a Member of the National Academy of Engineering.

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Moin, Parviz
Published by Cambridge University Press, 2010
ISBN 10: 0521711231 ISBN 13: 9780521711234
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Paperback. Condition: new. Paperback. Since the original publication of this book, available computer power has increased greatly. Today, scientific computing is playing an ever more prominent role as a tool in scientific discovery and engineering analysis. In this second edition, the key addition is an introduction to the finite element method. This is a widely used technique for solving partial differential equations (PDEs) in complex domains. This text introduces numerical methods and shows how to develop, analyse, and use them. Complete MATLAB programs for all the worked examples are now available at , and more than 30 exercises have been added. This thorough and practical book is intended as a first course in numerical analysis, primarily for new graduate students in engineering and physical science. Along with mastering the fundamentals of numerical methods, students will learn to write their own computer programs using standard numerical methods. This text introduces numerical methods and shows how to develop, analyse, and use them. Complete MATLAB programs are now available at , with more than 30 exercises. This thorough and practical book is a first course in numerical analysis for new graduate students in engineering and physical science. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780521711234

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