Higher Order Computational Electromagnetics, Uncertainty Quantification, and Meshing Techniques with Applications in Wireless Communication, Medicine, and Meteorology

摘要

We present some advances in several major components of computational electromagnetics (CEM), including (1) higher order method of moments, finite element method, ray-tracing, and hybrid techniques, (2) uncertainty quantification techniques for CEM modeling of RF and microwave devices and systems featuring a posteriori error estimation, sensitivity analysis, and intelligent model refinement based on adjoint methods, and (3) automatic surface meshing in CEM by the discrete surface Ricci flow method enabling generation of high quality meshes and adaptive iterative mesh refinement. We also show how these methodologies and techniques can be effectively applied to solving general real-world problems with impacts on wireless communication, medicine, and meteorology. The applications include (A) smart underground mining with an integrated wireless cyber-physical framework using CEM modeling and measurements of wireless propagation in underground mines, (B) design of RF coils for next-generation high and ultra-high field magnetic resonance imaging (MRI) scanners based on CEM and MRI experiments, and (C) accurate characterization of winter precipitation using multi-angle snowflake camera, visual hull image processing, advanced scattering methods, and polarimetric radar.