Tilmann Wittig

Two-step Lanczos algorithm for model order reduction

The Pade-Via-Lanczos (PVL) algorithm proved to be a reliable technique for obtaining reduced-order models of electromagnetic devices. Its computational complexity is, however, quite large, since it involves inversion or factorization of a matrix which can be, for complex devices, on the order of hundreds of thousands. The present paper proposes a two-step approach based entirely on the Lanczos algorithm, meant to drastically reduce the computational complexity. In the first step, a Lanczos-based projection technique is used to reduce the un-inverted matrix to a manageable size, which can be dealt with by the PVL method in the second step. The computing time was thus reduced by a factor of ten, as compared to the classical PVL.

An International Interlaboratory Comparison of Mobile Phone SAR Calculation With CAD-Based Models

An international interlaboratory comparison for numerical calculations of head phantom SAR involving three mobile phones with computer-aided design-based models has been conducted in order to evaluate the repeatability of such calculations and for providing input in the development of standardized procedures. SAR in the standardized specific anthropomorphic mannequin (SAM) head phantom was calculated by ten laboratories in a blind study manner. The agreement in calculated SAR between the participating laboratories is very similar to the agreement obtained in interlaboratory comparisons involving SAR measurements. The results support the opinion that standardized procedures for numerical calculations of SAR can be developed. The agreement between calculated SAR results and corresponding measurement results ranges from good to poor for the three phone models. Most probably, a significant reason for the observed deviations is the simplifications made to the models, which implies that device modeling specifications are of utmost importance in standards.

FIT/PVL circuit-parameter extraction for general electromagnetic devices

The most efficient technique for solving field-circuit coupled problems is to use an equivalent circuit for the electromagnetic device. This paper describes a general technique for determining reduced-order circuits starting from the field equations discretized with the Finite Integration Technique (FIT). Special boundary conditions ensure the good formulation of the coupled problem. Pade Via Lanczos (PVL) techniques are used for reducing the state-space form of the system. The proposed approach eliminates the need to actually solve the field problem in order to extract the parameters of the equivalent circuit.

Linearization of Parametric FIT-Discretized Systems for Model Order Reduction

Electrodynamic field simulations typically require the solution of large linear systems which may depend on several variables. Model Order Reduction Techniques offer an approach to solve these multivariate problems in a reasonable time. This paper presents an Order Reduction Method and the required system equation linearization for structures discretized by the Finite Integration Technique (FIT) depending on frequency and length variation.

A Benchmark CAD Mobile Phone Model for Specific Absorption Rate Calculations

Specific absorption rate (SAR) calculation using a computer-aided design (CAD)-based mobile phone model is still a challenging task. Seven international laboratories participated in an interlaboratory comparison of SAR calculations using a CAD-based model of a commercially available dual-band mobile phone. Return loss and peak 10 g average SAR results obtained using six different electromagnetic solvers were compared. Considering the differences in the techniques implemented in the solvers-either time or frequency domain-used for the interlaboratory comparison, overall a good agreement is observed. Proposed as a benchmark, results of the measured return loss and peak 10 g average SAR using the actual mobile phone are also provided.

Parametric Model Order Reduction by Neighbouring Subspaces

Electrodynamic field simulations in the frequency domain typically require the solution of large linear systems. Model Order Reduction (MOR) techniques offer a fast approach to approximate the system impedance with respect to the frequency parameter. Most commonly, MOR via projection is applied associated with certain Krylov projection matrices. During the design process it is desirable to vary specified parameters like the frequency, geometry details as well as material parameters, giving rise to multivariate dynamical systems. In this work, a multivariate MOR method is presented for parameterized systems based on the Finite Integration Technique (FIT). It utilizes the observation, that for small parameter variations the matrices associated with the univariate MOR differ only slightly. Thus, the multivariate MOR method is deduced from the usage of specified univariate subspaces.

Model order reduction methods for multivariate parameterized dynamical systems obtained by the finite integration theory

In electrodynamic field computations the continuous Maxwell equations are typically discretized in the space variables, i. e the continuous space is mapped onto a finite set of discrete elements leading to a system of differential equations constituting the Maxwell grid equations. These dynamical systems can be very large. Due to limited computational, accuracy and storage capabilities, simplified models, obtained by means of model order reduction (MOR) methods, which capture the main features of the original model are then successfully used instead of the original models. Most commonly MOR via projection is used. Variation of model parameters like geometrical or material parameters give rise to multivariate dynamical systems. It is aimed that also the simplified models keep this parameter dependence. In this work, MOR methods are presented for multivariate systems based on the finite integration technique (FIT). The methods are applied to numerical examples with both geometrical and material variations.

Threedimensional geometry variations of FIT systems for Model Order Reduction

Electrodynamic field simulations in the frequency domain typically require the solution of large linear systems. During the design process it is desirable to vary specified parameters like the frequency, geometry details as well as material parameters. Initializing an individual calculation to consider all parameter changes is not efficient. Model Order Reduction (MOR) techniques offer an approach to approximate the transfer function of these multivariate problems in reasonable time. Existing schemes for multivariate MOR require a linearization of the underlying system for systems based on the Finite Integration Technique (FIT). This paper focuses on the linearization for FIT-discretized systems, that depend on frequency and threedimensional rectilinear geometry variations and briefly discusses the utilized MOR techniques.

Standardization of Computational Techniques for Compliance Evaluation of the Human Exposure in Automotive Environments

This paper presents the recent efforts to develop standards allowing numerical methods and techniques for accurate and representative simulations of human exposure to RF energy in automotive environments. The focus of this work is to standardize numerical and modeling procedures that produce repeatable results based on simulations of the human body exposure to RF energy emitted by mobile radios with vehicle- mount antennas. This activity is carried out in the framework of IEEE 1528.1 and IEEE 1528.2 standards development with the goal to provide a robust methodology for evaluating the compliance of vehicle-mount transmitters with respect to international exposure safety standards by means of numerical simulations.

Bio-electromagnetic numerical analysis of body-worn antennas Including a 900 MHz RFID tag, a 2.4 GHz Wifi antenna and an UWB antenna

Presents the collection of slides covering the following topics: bioelectromagnetic numerical analysis; body-worn antennas; body area networks; phantoms; voxel; RFID antenna; ISM patch antenna; multiple antennas; communication networks; MIMO and UWB antenna.