A time domain method for quantitative analysis of geometrical uncertainty is introduced here by combining polynomial chaos expansion (PCE) with the radial point interpolation method (RPIM). The shape function matrix of RPIM is represented in a stochastic framework. The proposed method is validated in a two dimensional problem and its accuracy is compared with Monte-Carlo (MC) simulation using Kolmogorov Smirnov (KS) test. Time complexity of the proposed method is remarkably better than MC. Since RPIM is an unstructured node based approach, this method can be well adapted for complex curved geometries.
In this paper, a transceiver architecture suitable for future reconfigurable and programmable wireless communication and sensing systems is proposed and demonstrated. The two-dimensional (2D) distribution of both receiver (Rx) and transmitter (Tx) unit-cells enables the integration of multiple functions in a single transceiver topology, named Virtual Transceiver Matrix (VTM). The reason behind calling it "virtual" is rooted in a dynamic allocation of both modulating and demodulating unit-cells in this architecture. This allocation is dependent on the incoming signal properties and desired output radiations. Furthermore, the number of Rx and Tx channels is significantly increased compared to conventional fixed architectures. Mathematical modeling of VTM unit-cells is presented and simulations are performed to confirm the desired operation of the proposed topological transceiver.
In this contribution, we present a new approach to fully characterize interconnects composed out of arbitrary polygonal cross-sections and containing piecewise homogeneous material parameters. The complex per-unit-of-length inductance and capacitance matrices are obtained through the application of pertinent Dirichlet-to-Neumann operators, which are computed by means of an extended Fokas method, that are integrated in a boundary integral equation approach. As the complete RLGC-data of the structures under study is computed, we are able to assess relevant properties such as signal attenuation and cross-talk while the support for polygonal shapes allows for the inclusion of manufacturing effects such as etching.
In this paper, an ANN model development approach is outlined and studied for the development of tunable band-pass filter (tBPF). Circuit models are fast and efficient for design and optimization while physical models based on electromagnetic full-wave fields are accurate but computationally expensive and slow. In this work, an equivalent circuit model is developed from a full-wave tBPF structure. Then, equivalent circuit parameters are generated and mapped to tunable geometric parameters of the physical field model of the tBPF. The optimization is thus carried out on the equivalent circuit model. Finally, the geometric parameters are obtained by the ANN model from the optimized equivalent circuit parameters. A practical example of tBPF is used to demonstrate the proof of concept.
Numerous experimental parameters affect the accuracy of impedance measurements in scanning microwave micro-copy (SMM). Investigating their effects on the measured values is particularly challenging. Here, we present the development of a fully-numerical FEM-based environment as a digital-twin to the actual measurements in SMM. We demonstrate the application of a self-calibration procedure for the simulated measurements with a maximal deviation of ± 6 % relative to reference capacitances determined via electrostatic calculations. Furthermore, we show the possibility to simulate the effects of the tip apex geometry on the simulated SMM measurements.
