Abstract

We investigate efficient algorithms and a practical implementation of an explicit-type high-order timestepping method based on Krylov subspace approximations, for possible application to large-scale engineering problems in electromagnetics. We consider a semi-discrete form of the Maxwell's equations resulting from a high-order spectral-element discontinuous Galerkin discretization in space whose solution can be expressed analytically by a large matrix exponential of dimension $$\kappa \times \kappa $$ ? × ? . We project the matrix exponential into a small Krylov subspace by the Arnoldi process based on the modified Gram---Schmidt algorithm and perform a matrix exponential operation with a much smaller matrix of dimension $$m\times m$$ m × m ( $$m\ll \kappa $$ m ? ? ). For computing the matrix exponential, we obtain eigenvalues of the $$m\times m$$ m × m matrix using available library packages and compute an ordinary exponential function for the eigenvalues. The scheme involves mainly matrix-vector multiplications, and its convergence rate is generally $$O(\Delta t^{m-1})$$ O ( Δ t m - 1 ) in time so that it allows taking a larger timestep size as $$m$$ m increases. We demonstrate CPU time reduction compared with results from the five-stage fourth-order Runge---Kutta method for a certain accuracy. We also demonstrate error behaviors for long-time simulations. Case studies are also presented, showing loss of orthogonality that can be recovered by adding a low-cost reorthogonalization technique.

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