feflow_user_manual_classic.pdf

Séäçåáíó ééêçñáãíáçå kkk invokes

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sÉäçÅáíó ~ééêçñáã~íáçå KKK invokes the velocity-approximation options window where a selection of different evaluation methods for the computation of the local Darcy velocities is avail- able. `çåîÉÅíáîÉ Ñçêã íê~åëéçêí applies the default transport equations. These equa- tions are based on the continuity equation to eliminate portions of convective terms, creating a natural disper- sive-flux boundary condition. This option is recom- mended if mass transport can be formulated using first- type boundary conditions and zero dispersive fluxes along the remaining (outflowing) boundary sections. aáîÉêÖÉåÅÉ Ñçêã íê~åëéçêí invokes the divergence balance-improved formula- tion of the governing mass and heat transport equa- tions. This formulation describes a total boundary flux consisting of both convective and dispersive parts. This option is recommended when modeling the total (net) mass or heat flux along inflow boundary sections (e.g. waste injection or leakages from a disposal site, see Reference Manual for details). fíÉê~íáîÉ Éèì~íáçå ëçäîÉêë This (default) option is comprised of iterative equa- tion system solvers that are used during the FEM com- putational process. The symmetric sparse flow equations are commonly solved by a conjugate-gradi- ent method using incomplete Gauss-based precondi- tioning. As an alternative, FEFLOW also offers the algebraic multigrid SAMG solver . SAMG has proven very powerful for difficult problems where the conju- gate-gradient method takes a large number of iterations (poor convergence) or completely fails (divergence) 1) . The asymmetric sparse transport equations can be solved by a family of iterative techniques with incom- plete Crout-based preconditioning. The following solv- 1) for details see White Papers Vol. III, Chapter 3
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OM ö rëÉêÛë j~åì~ä J m~êí f OK pÜÉää ãÉåì ers are available: Restarted ORTHOMIN, restarted GMRES, CGS, BiCGSTAB, BiCGSTABP, and SAMG. BiCGSTABP is the default iterative solver for asym- metric problems. The iterative solvers are very effec- tive and reduce memory requirements. They are efficient for solving large problems containing more than about 20,000 nodes. The maximum iteration num- ber, available preconditioning method and the error cri- teria can be changed by using the Properties dialogs. As an alternative, the algebraic multigrid SAMG solver can be used for solving the transport equations. 1) aáêÉÅí Éèì~íáçå ëçäîÉê The Direct equation solver is best for small prob- lems (those with less than about 10,000 nodes). A Gaussian profile solver is used for both flow and trans- port equations. The Reverse Cuthill McKee (RCM) and, as an alternative, the Multilevel Nested Dissection (MLNDS) nodal reordering schemes are incorporated to minimize the matrix fill-in and the storage demand.
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