For an example that uses the Block low rank factorization see: Test Bench Car Interior. Application Library path Acoustics_Module/Automotive/test_bench_car_interior
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1
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Suggested Iterative Solver (GMRES with GMG): uses the GMRES iterative solver with a geometric multigrid (GMG) preconditioner. This method is typically faster than the direct solver and uses less memory for medium to large 3D models. For details, see Manual Setup of GMG Solver Suggestions and Theory.
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2
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Suggested Iterative Solver (FGMRES with GMG): uses the FGMRES iterative solver with a geometric multigrid (GMG) preconditioner. This method is more robust than GMRES, especially for problems that exhibit sharp resonances. If the GMRES suggestion does not converge try the FGMRES suggestion instead. For details, see Manual Setup of GMG Solver Suggestions and Theory.
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3
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Suggested Iterative Solver (Shifted Laplace): For increasing frequencies, the first two suggested iterative solvers, described above, will eventually stop converging. One solution is to use the complex shifted Laplacian (CSL or SL) method for the multigrid preconditioner. The SL method will in general speed up convergence for larger models. For details, see Complex Shifted Laplacian for Very Large Frequency Domain Models.
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4
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Suggested Iterative Solver (Domain Decomposition): This last suggestion is for solving very large models that need to run in a cluster (using a distributed architecture). The performance of the method will be best when used on several nodes. For details, see Domain Decomposition for Helmholtz on Clusters.
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If PMLs are present in the model solved with an iterative method, it is necessary to use the Polynomial scaling option (the default) and the recommended 8 mesh layers. This option will ensure proper convergence of the iterative methods. See the Perfectly Matched Layers (PMLs) section for further details.
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For models that run with a very fine frequency step (with a linear frequency distribution) it can be considered to change the Reuse solution from previous step option to Auto (or Yes). This will help convergence by providing a good initial guess for the iterative solvers.
However, in most cases for models that have a moderate spacing in the solved frequencies (and where frequencies are given on a logarithmic axis), the default option Off should be used. This setting will give the best performance in almost all cases.
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For an example that solves a model using an iterative solver see: Headphone on an Artificial Ear. Application Library path Acoustics_Module/Electroacoustic_Transducers/headphone_artificial_ear
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For further details see Complex Shifted Laplacian for Large Helmholtz Problems section in the COMSOL Multiphysics Reference Manual.
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For further details see Complex Shifted Laplacian for Large Helmholtz Problems section in the COMSOL Multiphysics Reference Manual.
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Geometric multigrid as a linear system solver (set the Solver selection to Use preconditioner) with GMRES as a smoother. Under the Multigrid node right-click the Presmoother and Postsmoother nodes and select the Krylov Preconditioner with the Solver selection to GMRES.
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FGMRES as a linear system solver (set the Solver selection to FGMRES) with geometric multigrid as a preconditioner (where GMRES is used as a smoother, as above).
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If the Nyquist criterion is fulfilled on the coarsest mesh, try to use geometric multigrid as a linear system solver (set Multigrid as preconditioner and set the linear system solver to Use preconditioner) with default smoothers. The default smoothers are fast and have small memory requirements.
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