Correct 2018 bugs in modal analysis and hmogenization

parent 874cba7d
 ... @@ -106,15 +106,13 @@ can be solved using the SLEPcEigenSolver. :: ... @@ -106,15 +106,13 @@ can be solved using the SLEPcEigenSolver. :: eigensolver = SLEPcEigenSolver(K, M) eigensolver = SLEPcEigenSolver(K, M) eigensolver.parameters['problem_type'] = 'gen_hermitian' eigensolver.parameters['problem_type'] = 'gen_hermitian' eigensolver.parameters["spectrum"] = "smallest real" eigensolver.parameters['spectral_transform'] = 'shift-and-invert' eigensolver.parameters['spectral_transform'] = 'shift-and-invert' eigensolver.parameters['spectral_shift'] = 0. eigensolver.parameters['spectral_shift'] = 0. The problem type is specified to be a generalized eigenvalue problem with The problem type is specified to be a generalized eigenvalue problem with Hermitian matrices. By default, SLEPc computes the largest eigenvalues, here Hermitian matrices. By default, SLEPc computes the largest eigenvalues. Here we instead look for the smallest eigenvalues (they should all be real). To we instead look for the smallest eigenvalues (they should all be real). A improve convergence of the eigensolver for finding the smallest eigenvalues spectral transform is therefore performed (by default it computes the largest ones), a spectral transform is performed using the keyword shift-invert i.e. the original problem is transformed into using the keyword shift-invert i.e. the original problem is transformed into an equivalent problem with eigenvalues given by :math:\dfrac{1}{\lambda - \sigma} an equivalent problem with eigenvalues given by :math:\dfrac{1}{\lambda - \sigma} instead of :math:\lambda where :math:\sigma is the value of the spectral shift. instead of :math:\lambda where :math:\sigma is the value of the spectral shift. ... ...
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