BDDC

In numerical analysis, BDDC (balancing domain decomposition by constraints) is a domain decomposition method for solving large symmetric, positive definite systems of linear equations that arise from the finite element method. BDDC is used as a preconditioner to the conjugate gradient method. A specific version of BDDC is characterized by the choice of coarse degrees of freedom, which can be values at the corners of the subdomains, or averages over the edges or the faces of the interface between the subdomains. One application of the BDDC preconditioner then combines the solution of local problems on each subdomains with the solution of a global coarse problem with the coarse degrees of freedom as the unknowns. The local problems on different subdomains are completely independent of each other, so the method is suitable for parallel computing. With a proper choice of the coarse degrees of freedom (corners in 2D, corners plus edges or corners plus faces in 3D) and with regular subdomain shapes, the condition number of the method is bounded when increasing the number of subdomains, and it grows only very slowly with the number of elements per subdomain. Thus the number of iterations is bounded in the same way, and the method scales well with the problem size and the number of subdomains. In numerical analysis, BDDC (balancing domain decomposition by constraints) is a domain decomposition method for solving large symmetric, positive definite systems of linear equations that arise from the finite element method. BDDC is used as a preconditioner to the conjugate gradient method. A specific version of BDDC is characterized by the choice of coarse degrees of freedom, which can be values at the corners of the subdomains, or averages over the edges or the faces of the interface between the subdomains. One application of the BDDC preconditioner then combines the solution of local problems on each subdomains with the solution of a global coarse problem with the coarse degrees of freedom as the unknowns. The local problems on different subdomains are completely independent of each other, so the method is suitable for parallel computing. With a proper choice of the coarse degrees of freedom (corners in 2D, corners plus edges or corners plus faces in 3D) and with regular subdomain shapes, the condition number of the method is bounded when increasing the number of subdomains, and it grows only very slowly with the number of elements per subdomain. Thus the number of iterations is bounded in the same way, and the method scales well with the problem size and the number of subdomains. BDDC was introduced by different authors and different approches at about the same time, i.e., by Cros, Dohrmann, and Fragakis and Papadrakakis, as a primal alternative to the FETI-DP domain decomposition method by Farhat et al. See for a proof that these are all actually the same method as BDDC. The name of the method was coined by Mandel and Dohrmann, because it can be understood as further development of the BDD (balancing domain decomposition) method. Mandel, Dohrmann, and Tezaur proved that the eigenvalues of BDDC and FETI-DP are identical, except for the eigenvalue equal to one, which may be present in BDDC but not for FETI-DP, and thus their number of iterations is practically the same. Much simpler proofs of this fact were obtained later by Li and Widlund and by Brenner and Sung. The coarse space of BDDC consists of energy minimal functions with the given values of the coarse degrees of freedom. This is the same coarse space as used for corners in a version of BDD for plates and shells. The difference is that in BDDC, the coarse problem is used in an additive fashion, while in BDD, it is used a multiplicatively. The BDDC method is often used to solve problems from linear elasticity, and it can be perhaps best explained in terms of the deformation of an elastic structure. The elasticity problem is to determine the deformation of a structure subject to prescribed displacements and forces applied to it. After applying the finite element method, we obtain a system of linear algebraic equations, where the unknowns are the displacements at the nodes of the elements and the right-hand side comes from the forces (and from nonzero prescribed displacements on the boundary, but, for simplicity, assume that these are zero).