Abstract
Computational methods and algorithms are quickly becoming a necessity in science and engineering fields. These modeling techniques not only take the computational onus from the human brain, but can also provide visualizations for the problem at hand. This research thesis delves into the facets of these computing processes, specifically at the intersection of electromagnetic applications and iterative computational modeling. By first laying the groundwork for governing electrostatic equations, a general overview of surface charge distribution is discussed, and the need for accurate modeling techniques in this field is reviewed. Afterwards, some common algorithm types are analyzed, including finite element analysis and basic iterative computational structures. The heart of the thesis is devoted to merging a surface charge distribution code with a Python based meshing algorithm to create a novel code meant for determining surface charge distribution and electric field in a realistic, wire-like domain. Prior to this analysis, the Ruth Chabay and Bruce Sherwood surface charge distribution code is examined. Similarly, the Python based meshing package, called PyDistMesh, is explained. Finally, with these two software pillars thoroughly understood, the novelty and effectiveness of the combined code is assessed. The work done here aims to build a proof of concept model for determining surface charge distribution and electric field in a wire like domain, as opposed to past models that used geometries with corners. Though the final product looks solely at electrostatic situations, the ultimate goal would be to model the steady state surface charge distribution in a circuit-like domain.