Neumann–Neumann Methods
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In mathematics, Neumann–Neumann methods are domain decomposition
preconditioner In mathematics, preconditioning is the application of a transformation, called the preconditioner, that conditions a given problem into a form that is more suitable for numerical solving methods. Preconditioning is typically related to reducing ...
s named so because they solve a Neumann problem on each subdomain on both sides of the interface between the subdomains.A. Klawonn and O. B. Widlund, ''FETI and Neumann–Neumann iterative substructuring methods: connections and new results'', Comm. Pure Appl. Math., 54 (2001), pp. 57–90. Just like all domain decomposition methods, so that the number of iterations does not grow with the number of subdomains, Neumann–Neumann methods require the solution of a coarse problem to provide global communication. The
balancing domain decomposition In numerical analysis, the balancing domain decomposition method (BDD) is an iterative method to find the solution of a symmetric positive definite system of linear algebraic equations arising from the finite element method.J. Mandel, ''Balancing d ...
is a Neumann–Neumann method with a special kind of coarse problem. More specifically, consider a domain Ω, on which we wish to solve the Poisson equation :-\Delta u = f, \qquad u, _ = 0 for some function ''f''. Split the domain into two non-overlapping subdomains Ω1 and Ω2 with common boundary Γ and let ''u''1 and ''u''2 be the values of ''u'' in each subdomain. At the interface between the two subdomains, the two solutions must satisfy the matching conditions :u_1 = u_2, \qquad \partial_u_1 = \partial_u_2 where n_ is the unit normal vector to Γ in each subdomain. An iterative method with iterations k=0,1,... for the approximation of each ui (i=1,2) that satisfies the matching conditions is to first solve the Dirichlet problems :-\Delta u_i^ = f_i \; \text \; \Omega_, \qquad u_i^, _ = 0, \quad u^_i, _\Gamma = \lambda^ for some function λ(k) on Γ, where λ(0) is any inexpensive initial guess. We then solve the two Neumann problems :-\Delta\psi_i^ = 0 \; \text \; \Omega_ , \qquad \psi_i^, _ = 0, \quad \partial_\psi_i^, _ = \omega(\partial_u_1^ + \partial_u_2^). We then obtain the next iterate by setting :\lambda^ = \lambda^ - \omega(\theta_1\psi_1^ + \theta_2\psi_2^) \; \text \; \Gamma for some parameters ω, θ1 and θ2. This procedure can be viewed as a
Richardson iteration Modified Richardson iteration is an iterative method for solving a system of linear equations. Richardson iteration was proposed by Lewis Fry Richardson in his work dated 1910. It is similar to the Jacobi and Gauss–Seidel method. We seek the so ...
for the iterative solution of the equations arising from the Schur complement method.A. Quarteroni and A. Valli, ''Domain Decomposition Methods for Partial Differential Equations'', Oxford Science Publications 1999. This continuous iteration can be discretized by the
finite element method The finite element method (FEM) is a popular method for numerically solving differential equations arising in engineering and mathematical modeling. Typical problem areas of interest include the traditional fields of structural analysis, heat ...
and then solved—in parallel—on a computer. The extension to more subdomains is straightforward, but using this method as stated as a preconditioner for the Schur complement system is not scalable with the number of subdomains; hence the need for a global coarse solve.


See also

* Neumann–Dirichlet method


References

{{DEFAULTSORT:Neumann-Neumann Methods Domain decomposition methods