Near-Field PML Optimization for Low and High Order FDTD Algorithms Using Closed-Form Predictive Equations

The convolutional perfectly-matched-layer (CPML) absorbing boundary condition is fully capable of handling near-field wave absorption that usually combines near-grazing wave incidence with wave evanescence. The appropriate choice of the various CPML parameters to realize this potential for any given simulation problem is a challenging task that is typically achieved through exhaustive and time-consuming searches that involve large numbers of full-scale simulations. The presented work here uses a previously developed predictive system of equations that accurately determines numerical reflections off the PML interface and embeds it into a global optimization routine that reliably computes the required optimum CPML parameters. This predictive system of equations has also been extended and validated for the M24 and FV24 integral-based high-order FDTD algorithms. With this approach, the task of selecting optimum CPML parameters that would usually take several days of intense computations can now be accomplished within a few minutes on an average personal computer.