Decomposition Methods for Differential Equations

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A01=Juergen Geiser
A2 Ei
ADI Method
advanced differential equation solver applications
Author_Juergen Geiser
banach
Banach Space
benchmark problems
boundary value problem methods
C0 Semigroup
Category=PB
Category=PBKJ
Category=UB
cauchy
CFL Condition
decomposistion methods
Decomposition Methods
Discontinuous Galerkin Methods
Discretization Methods
elastic
Elastic Wave Propagation
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Evolution Equations
Galerkin Method
hyperbolic equation solutions
Iteration Steps
iterative
Iterative Splitting
Iterative Splitting Method
LOD Method
MATLAB computational experiments
multi-physics problems
Nonlinear Semigroup
numerical experiments
numerical stability analysis
operator
Operator Splitting Method
parabolic equation modeling
PDE
Physical Vapor Transport
problem
Proposed Decomposition Methods
PVT
semigroup
space
spatial discretization techniques
Split Approximation
splitting
Splitting Method
Unbounded Operators
wave

Product details

  • ISBN 9781138114142
  • Weight: 590g
  • Dimensions: 156 x 234mm
  • Publication Date: 14 Jun 2017
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Decomposition Methods for Differential Equations: Theory and Applications describes the analysis of numerical methods for evolution equations based on temporal and spatial decomposition methods. It covers real-life problems, the underlying decomposition and discretization, the stability and consistency analysis of the decomposition methods, and numerical results.

The book focuses on the modeling of selected multi-physics problems, before introducing decomposition analysis. It presents time and space discretization, temporal decomposition, and the combination of time and spatial decomposition methods for parabolic and hyperbolic equations. The author then applies these methods to numerical problems, including test examples and real-world problems in physical and engineering applications. For the computational results, he uses various software tools, such as MATLAB®, R3T, WIAS-HiTNIHS, and OPERA-SPLITT.

Exploring iterative operator-splitting methods, this book shows how to use higher-order discretization methods to solve differential equations. It discusses decomposition methods and their effectiveness, combination possibility with discretization methods, multi-scaling possibilities, and stability to initial and boundary values problems.

Jürgen Geiser is a professor in the Department of Mathematics at Humboldt University of Berlin.

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