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The Least-Squares Finite Element Method: Theory and Applications in Computational Fluid Dynamics and Electromagnetics (Scientific Computation)
 
 
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The Least-Squares Finite Element Method: Theory and Applications in Computational Fluid Dynamics and Electromagnetics (Scientific Computation) [Hardcover]

Bo-nan Jiang (Author)
5.0 out of 5 stars  See all reviews (1 customer review)

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Book Description

June 22, 1998 3540639349 978-3540639343 1
This is the first monograph on the subject, providing a comprehensive introduction to the LSFEM method for numerical solution of PDEs. LSFEM is simple, efficient and robust, and can solve a wide range of problems in fluid dynamics and electromagnetics.

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From the Back Cover

This is the first book devoted to the least-squares finite element method (LSFEM), which is a simple, efficient and robust technique for the numerical solution of partial differential equations. The book demonstrates that the LSFEM can solve a broad range of problems in fluid dynamics and electromagnetics with only one mathematical/computational formulation. The book shows that commonly adopted special treatments in computational fluid dynamics and computational electromagnetics, such as upwinding, numerical dissipation, staggered grid, non-equal-order elements, operator splitting and preconditioning, edge elements, vector potential, and so on, are unnecessary. This book introduces the basic theory of the least-squares method for first-order PDE systems, particularly the div-curl system and the div-curl-grad system. It is applied to the study of permissible boundary conditions for the incompressible Navier--Stokes equations, to show that the divergence equations in the Maxwell equations are not redundant, and to derive equivalent second-order versions of the Navier--Stokes equations and the Maxwell equations. This book covers diverse applications such as incompressible viscous flows, rotational inviscid flows, low- or high-Mach-number compressible flows, two-fluid flows, convective flows, and scattering waves.

Product Details

  • Hardcover: 434 pages
  • Publisher: Springer; 1 edition (June 22, 1998)
  • Language: English
  • ISBN-10: 3540639349
  • ISBN-13: 978-3540639343
  • Product Dimensions: 9.5 x 6.3 x 1.1 inches
  • Shipping Weight: 1.6 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #1,944,679 in Books (See Top 100 in Books)

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5 of 8 people found the following review helpful:
5.0 out of 5 stars This is an important book !, July 29, 1998
By A Customer
This review is from: The Least-Squares Finite Element Method: Theory and Applications in Computational Fluid Dynamics and Electromagnetics (Scientific Computation) (Hardcover)
Why so? It draws attention to the use of the least-squares method for the solution of problems in fluid mechanics and electromagnetics. This method promises a remarkable simplification in the use of the finite element method in these fields as well as a unification with other fields such as structural analysis. Regardless of your prior experience with cfm or cem, this approach should be tried before you settle on any given approach.
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Inside This Book (learn more)
First Sentence:
Why Finite Elements? Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
finite element collocation method, bounded inverse theorem, permissible boundary conditions, bilinear elements, two divergence equations, trilinear elements, convective transport problems, standard matrix form, reattachment length, variational statement, spurious solutions, preconditioned conjugate gradient method, compressible viscous flows, vorticity contours, curl equations, resulting algebraic equations, vorticity formulation, central difference method, nodal values, primal variable, numerical dissipation, interface profile, computational electromagnetics, cavity flow, orthogonal condition
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Concluding Remarks, The First-Order Governing Equations, Model Problem Let
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