Eric Laermans

Numerical and experimental study of the shielding effectiveness of a metallic enclosure

This paper presents a detailed study of the shielding effectivity properties of metal enclosures. Measurements in anechoic chambers are compared to full-wave electromagnetic simulations. The study is not limited to the frequency range below the first resonance frequency. Different aspects are investigated such as the influence of the size, position and number of apertures, and the effect of the presence of metal plates and of absorbing materials. Where possible, the specific behavior of the shielding effectivity is explained theoretically and existing simple design rules are assessed.

Efficient space-filling and non-collapsing sequential design strategies for simulation-based modeling

Simulated computer experiments have become a viable cost-effective alternative for controlled real-life experiments. However, the simulation of complex systems with multiple input and output parameters can be a very time-consuming process. Many of these high-fidelity simulators need minutes, hours or even days to perform one simulation. The goal of global surrogate modeling is to create an approximation model that mimics the original simulator, based on a limited number of expensive simulations, but can be evaluated much faster. The set of simulations performed to create this model is called the experimental design. Traditionally, one-shot designs such as the Latin hypercube and factorial design are used, and all simulations are performed before the first model is built. In order to reduce the number of simulations needed to achieve the desired accuracy, sequential design methods can be employed. These methods generate the samples for the experimental design one by one, without knowing the total number of samples in advance. In this paper, the authors perform an extensive study of new and state-of-the-art space-filling sequential design methods. It is shown that the new sequential methods proposed in this paper produce results comparable to the best one-shot experimental designs available right now.

Modeling differential via holes

In this paper, we present a method to characterize differential via holes in printed circuit boards in a both fast and accurate way. The via hole is modeled as a cascade of capacitances and inductances. We use FASTCAP to compute the values of the capacitances, and a closed form formula to obtain the inductance values. The numerical predictions are compared with experimental data.

Modelling complex via hole structures

Derives a physics-based circuit model for complex via hole structures in printed circuit boards. The via hole is modeled as a cascade of capacitance and inductance matrices. Capacitance values are computed using a three-dimensional electrostatic solver and inductance values are computed from a two-dimensional quasi-TEM solver. This model is valid at frequencies up to a few gigahertz for typical via hole geometries, where the return current follows a well defined path.

Automated linear regression tools improve RSSI WSN localization in multipath indoor environment

Received signal strength indication (RSSI)-based localization is emerging in wireless sensor networks (WSNs). Localization algorithms need to include the physical and hardware limitations of RSSI measurements in order to give more accurate results in dynamic real-life indoor environments. In this study, we use the Interdisciplinary Institute for Broadband Technology real-life test bed and present an automated method to optimize and calibrate the experimental data before offering them to a positioning engine. In a preprocessing localization step, we introduce a new method to provide bounds for the range, thereby further improving the accuracy of our simple and fast 2D localization algorithm based on corrected distance circles. A maximum likelihood algorithm with a mean square error cost function has a higher position error median than our algorithm. Our experiments further show that the complete proposed algorithm eliminates outliers and avoids any manual calibration procedure.

Multiobjective global surrogate modeling, dealing with the 5-percent problem

When dealing with computationally expensive simulation codes or process measurement data, surrogate modeling methods are firmly established as facilitators for design space exploration, sensitivity analysis, visualization, prototyping and optimization. Typically the model parameter (=hyperparameter) optimization problem as part of global surrogate modeling is formulated in a single objective way. Models are generated according to a single objective (accuracy). However, this requires an engineer to determine a single accuracy target and measure upfront, which is hard to do if the behavior of the response is unknown. Likewise, the different outputs of a multi-output system are typically modeled separately by independent models. Again, a multiobjective approach would benefit the domain expert by giving information about output correlation and enabling automatic model type selection for each output dynamically. With this paper the authors attempt to increase awareness of the subtleties involved and discuss a number of solutions and applications. In particular, we present a multiobjective framework for global surrogate model generation to help tackle both problems and that is applicable in both the static and sequential design (adaptive sampling) case.

Fast shielding effectiveness prediction for realistic rectangular enclosures

A fast, semianalytical method to predict the shielding in the low-frequency and multiresonant region of realistic enclosures with many small apertures is presented. The method is based on previous work by Mendez. The validity of an often used rule of thumb for arrays of apertures is discussed and a comparison with full-wave method of moment simulations is provided.

Modelling differential via holes

With the ever-increasing frequencies of printed circuit board (PCB) interconnections, the role played by via holes is no longer negligible. Thoughtless design of via holes on a board may seriously degrade signal integrity due to reflections, ground bounce, etc. However, the characterisation of via holes has not drawn much attention until now. This paper presents a method for the characterisation of differential via holes as a cascade of capacitances and inductances. Capacitances are computed using FASTCAP and inductances using simple analytical models.

Recovering lossy multiconductor transmission line parameters from impedance or scattering representations

In this paper, we present a generalization of the simultaneous diagonalization technique by means of congruence transformations to the general reciprocal lossy multiconductor transmission line case. The method paves the way to solving the inverse problem, i.e., given a lossy multiconductor transmission line system of a given length, recover the transmission line parameters from the impedance or scattering descriptions.

Performance study of gradient-enhanced Kriging

Abstract The use of surrogate models for approximating computationally expensive simulations has been on the rise for the last two decades. Kriging-based surrogate models are popular for approximating deterministic computer models. In this work, the performance of Kriging is investigated when gradient information is introduced for the approximation of computationally expensive black-box simulations. This approach, known as gradient-enhanced Kriging, is applied to various benchmark functions of varying dimensionality (2D-20D). As expected, results from the benchmark problems show that additional gradient information can significantly enhance the accuracy of Kriging. Gradient-enhanced Kriging provides a better approximation even when gradient information is only partially available. Further comparison between gradient-enhanced Kriging and an alternative formulation of gradient-enhanced Kriging, called indirect gradient-enhanced Kriging, highlights various advantages of directly employing gradient information, such as improved surrogate model accuracy, better conditioning of the correlation matrix, etc. Finally, gradient-enhanced Kriging is used to model 6- and 10-variable fluid–structure interaction problems from bio-mechanics to identify the arterial wall’s stiffness.