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Power diagrams are a generalization of Voronoi diagrams for arbitrary dimensions. We present a modeling and optimization scheme for power diagrams in three spacial dimensions based on the statistics of experimental data obtained from cross-sectional images of polycrystalline materials. Our optimization scheme based on the grains' area and perimeter distributions can be used to obtain realistic three-dimensional polycrystalline structures which can subsequently be used for numerical simulations. As a proof of the concept we apply our scheme to high-performance ceramics and present the results of initial shock-impact simulations of the obtained polycrystalline structures

In this paper an approach for stability analysis of power systems for " More Electric Aircraft " (MEA) using µ sensitivity is proposed. The application of the proposed approach is illustrated via a regulated buck converter as a typical critical component in a power system. Due to the negative resistance at low frequencies the regulated buck converter could be unstable in combination with the input filter. A typical regulated buck converter is first modelled in the simulation package Dymola. The model equations are transferred to Maple or Matlab with a Dymola toolbox and symbolically linearized at steady state conditions. For computing µ sensitivity it is necessary to get a Linear Fractional Representation (LFR) of the buck converter. This is done by using the enhanced LFR Toolbox 2.0. Finally, the µ sensitivity is computed with the Robust Control Toolbox 3.1.1 of Mathworks. Compared with other methods for small signal stability, e.g. Middlebrook criterion and Modal Analysis, the µ sensitivity approach gives a much more global and direct result for the influence of all components on stability.

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