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    Fast Direct H-Matrix Solvers for Computational Electromagnetics
    In this project, fast direct solvers based on hierarchical (H-) matrices are investigated and extended to cope with arbitrary boundary conditions. The goal of the project is a fast electromagnetic solver based on the method of moments (MoM) that is applicable to a wide range of problems. These solvers are particularly interesting for highly resonant structures such as personal computer systems, as iterative solvers show a poor convergence. Furthermore, these systems comprise various components which leads to a high complexity of the simulation setup. Typical components include lossy dielectric and metallic materials, printed circuit boards, cables, and structural components. These are confined in the narrow space of the cavity and impact on the standing pattern. In this scenario, fast numerical methods based on multi-pole expansion of the far field are not feasible and algebraic methods such as the adaptive cross approximation need to be applied. The resulting H-matrices can be efficiently used to solve the MoM system matrix. The implemented solver is part of the Concept-II framework and shows an excellent performance for all frequencies and simulation scenarios a traditional (full) MoM solver can be applied to.
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    Analysis of Electromagnetic Interference in Server Casings
    With increasing data rates EM emission has become a major issue for EMC and EMI considerations in current server designs. Major sources of EM emission inside include ICs, cables and connectors, and Printed Circuit Boards. While efficient techniques exist to model the interior coupling of PCB cavities (Zpp ), the external (3D) coupling still has to be computed using full-wave techniques. This project aims to combine the different methods to model and simulate the components of the server. The dimensions and high data rates in addition to the high complexity of the individual components encountered in modern servers lead to a number of unknowns that are commonly in the range of several million. Therefore, efficient numerical methods and approximate models have to be developed.
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