Karol Aniserowicz

Comparison of Lightning-Induced Current Simulations in the Time and Frequency Domains Using Different Computer Codes

A simulation of lightning-caused currents and fields with the use of seven commonly applied computer codes (NEC-2, NEC-4, AWAS-2, CDEGS, WIPL-D, MININEC, and FEKO) is presented. Near-field computations in a wide-frequency band from 100 Hz to 10 MHz with the assumption of perfectly conducting ground are performed. Similarities and discrepancies of computation results observed both in the time and frequency domains are described. The discrepancies originate from the application of different approximation techniques. Numerical problems are compared using an example of a loop located inside a lightning protection system directly hit by lightning. The paper is supplemented by a short description of the computer programs and two examples with analytical solution validating the numerical results.

Investigation of Models of Grid-Like Shields Subjected to Lightning Electromagnetic Field: Experiments in the Frequency Domain

In this paper, frequency-domain measurements of magnetic and electric field shielding effectiveness of grid-like spatial shield models exposed to lightning action are presented. Scaled experimental models of nearby and direct lightning strikes are proposed. Models of single-layer and double-layer wire shields of two different mesh widths are examined. Differences between the shielding effectiveness of magnetic and electric fields are discussed. The measurement results are compared to the results of numerical simulations.

Computer Analysis of Electromagnetic Field Inside LPS Directly Stroke by Lightning

Shielding effected by a lightning protection system (LPS) during a direct lightning strike is analyzed. Reduction of electric and magnetic fields within a zone surrounded by a LPS has been evaluated using the method of moments in the frequency domain. The time-domain waveforms have been obtained by the DFT. The results are compared to the formulas presented in 1EC/TS 61312-2.

Analysis of differences in results of measurements and calculations of slotted enclosure shielding effectiveness

An impact of physical imperfections of a slotted enclosure on results of measurements and computations of the enclosure shielding effectiveness (SE) is examined. Small changes of direction of illumination by a plane wave and of selected geometrical dimensions are analyzed numerically and compared to results of measurements in a GTEM cell test site. The Feature Selective Validation (FSV) method is used for qualitative and quantitative comparison of measured and computed results.

Comments on "Analysis of lightning-radiated electromagnetic fields in the vicinity of lossy ground"

For original paper see Shoory et al. (IEEE Trans. Electromagn. Compat., vol.47, no.4, p.131-44, 2005 February).

The Feature Selective Validation Technique as Analysis Tool for Shielding Effectiveness of Slotted Enclosures

The results of feature selective validation (FSV) technique are used as analysis tools to identify the influence of differences and/or imperfections in the results between measurement setup and simulation models for the evaluation of shielding effectiveness in slotted enclosures. The experiments are carried out on the enclosure placed in the gigahertz transverse electromagnetic (GTEM) cell. A new technique for the evaluation of the shielding of a slotted enclosure is proposed. The enclosure under test is equipped with a built-in, rotating, and conductive stirrer, and the shielding is measured or computed at discrete angles of the stirrer. The stirrer is used for modeling different internal arrangements of the enclosure and for an approximation of the “worst case” of the shielding performance.

Downsampled and Undersampled Datasets in Feature Selective Validation (FSV)

Feature selective validation (FSV) is a heuristic method for quantifying the (dis)similarity of two datasets. The computational burden of obtaining the FSV values might be unnecessarily high if datasets with large numbers of points are used. While this may not be an important issue per se it is an important issue for future developments in FSV such as real-time processing or where multidimensional FSV is needed. Coupled with the issue of dataset size, is the issue of datasets having “missing” values. This may come about because of a practical difficulty or because of noise or other confounding factors making some data points unreliable. These issues relate to the question “what is the effect on FSV quantification of reducing or removing data points from a comparison-i.e., down- or undersampling data?” This paper uses three strategies to achieve this from known datasets. This paper demonstrates, through a representative sample of 16 pairs of datasets, that FSV is robust to changes providing a minimum dataset size of approximately 200 points is maintained. It is robust also for up to approximately 10% “missing” data, providing this does not result in a continuous region of missed data.