V. M. Krushnarao Kotteda, Vinod Kumar, William Spotz, "Performance of preconditioned iterative solvers in MFiX–Trilinos for fluidized beds", The Journal of Supercomputing (2018) 74: 4104. https://doi.org/10.1007/s11227-018-2415-5
Abstract: MFiX, a general-purpose Fortran-based suite, simulates the complex flow in fluidized bed applications via BiCGStab and GMRES methods along with plane relaxation preconditioners. Trilinos, an object-oriented framework, contains various first- and second-generation Krylov subspace solvers and preconditioners. We developed a framework to integrate MFiX with Trilinos as MFiX does not possess advanced linear methods. The framework allows MFiX to access advanced linear solvers and preconditioners in Trilinos. The integrated solver is called MFiX–Trilinos, here after. In the present work, we study the performance of variants of GMRES and CGS methods in MFiX–Trilinos and BiCGStab and GMRES solvers in MFiX for a 3D gas–solid fluidized bed problem. Two right preconditioners employed along with various solvers in MFiX–Trilinos are Jacobi and smoothed aggregation. The flow from MFiX–Trilinos is validated against the same from MFiX for BiCGStab and GMRES methods. And, the effect of the preconditioning on the iterative solvers in MFiX–Trilinos is also analyzed. In addition, the effect of left and right smoothed aggregation preconditioning on the solvers is studied. The performance of the first- and second-generation solver stacks in MFiX–Trilinos is studied as well for two different problem sizes.
Keywords: Linear solvers Preconditioners MFiX–Trilinos Trilinos MFiX Fluidized beds Distributed memory computing