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Item type:Publication, Access status: without files , Identification of critical frequencies in wideband near-field spatial scans(IEEE, 2026-03-31); ; ; ; Identifying critical frequencies of a device under test (DUT) from its near-field scans is an essential step in integrating near-field scanning into electromagnetic compatibility (EMC) testing. Indeed, real electronic devices may exhibit radiated emissions at multiple frequencies, which are unknown a priori. To this end, three computational methods are introduced to identify the frequencies at which the DUT is radiating: the space-filled spectrogram analysis, the grey level co-occurrence matrix approach, and spatial fast Fourier transform approach. Although a single general solution is not provided, each method leverages different properties of the measurements to extract significant features and identify frequencies of interest. Therefore, the choice of which method to apply depends on the characteristics of the DUT and on the requirements of the specific measurement campaign. The proposed methods are evaluated on a common dataset, assessing their computational efficiency, sensitivity to patterns, and robustness against noise. Case studies demonstrate their successful application in real-world scenarios and their comparative analysis provides insights into selecting the most appropriate approach for a specific application.Publicationtype: Journal Article9 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Morphological Search for Near-Field Equivalent Infinitesimal Dipole ModelsNear-field modeling techniques have proven to be very useful for electromagnetic compatibility evaluation. In this article, a new method for building infinitesimal dipolemodels using near-field phaseless scans is presented. The proposed approach enables the identification of optimal dipole source locations by comparing the pattern of an infinitesimal dipole with the measured field maps. Finally, the dipole moments are fitted by using the Levenberg–Marquardt algorithm. This method is validated on two different virtual devices and on measurements from a real device. These test cases cover a range of frequencies (156, 381, 514, and 1 GHz) and scan dimensions (9.4 cm × 8.4 cm and 10.6 cm × 14 cm), demonstrating the robustness and versatility of the proposed method.Publicationtype: Journal Article24 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Machine Learning based data validation for signal integrity and power integrity using supervised time series classificationA novel approach for the validation of data in signal integrity and power integrity using machine learning is proposed. This approach presents an alternative to the feature selective validation method outlined in the IEEE Standard 1597.1 for the validation of computational electromagnetics,computer modeling and simulations. The proposed approach focuses on replicating the human visual assessment by using data collected and labeled by expert engineers to train time series classification networks that predict the degree of agreement between two curves. The trained networks are then used for the systematic and automated validation of 1-D datasets. The performance and suitability of this approach for systematic data validation is evaluated and discussed. The trained network surpasses the single human subjects in predicting the expert opinion with an accuracy higher than 70%.Publicationtype: Journal Article38 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Generation and application of a very large dataset for signal integrity via array and link analysis(IEEE, 2024-09-18); ; ; ; In this article, a physics inspired and data-driven analysis is performed using a very large dataset of printed circuit board (PCB) based high-speed interconnects. Three different subsets are defined having approximately 15000 PCB material and geometry variations. To the authors' knowledge, this dataset is the largest ever generated and applied dataset for signal integrity (SI) purposes. The dataset is generated using accurate physics based (PB) modeling up to 60 ,mathrm{G}mathrm{Hz} and provided for download in the SI/PI-Database. The first two subsets consist of a single-ended and a differential via array with up to 116 ports with arbitrary positions for signal, power, and ground vias. The third subset represents a link over differential transmission lines between two via arrays. A data and machine learning (ML) analysis is performed showing the dependencies between the PCB parameters and clock frequency of PCI Gen 6. The large and realistic defined design spaces reflect the high complexity and dimensionality of the SI design problems and allow multipurpose ML-based analysis.Publicationtype: Journal Article20 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Efficient Iterative Data Generation Using Evaluation of Prioritized Input Parameters in ANNs for SAR Prediction in Human Head Models at 13.56 MHzIn this work, an efficient iterative dataset generation strategy is proposed, considering prediction accuracy and high impact input parameters as figures of merit to define a sufficient number of samples for reliable machine learning (ML) results. Parameter prioritization in combination with artificial neural networks (ANNs) is designed for examination of multiparameterized simulation setups in bioelectromagnetic (BEM), aiming to avoid redundant parameters and excessive sample sizes and to provide an alternative to expensive measurements, full-wave simulations, and the limitations of adaptive sampling methods in high-dimensional BEM problems. Specifically, the variation of mass-averaged specific absorption ratio (SAR) in each individual tissue in human head models is studied, considering up to ±\pm 95% uncertainty in a uniform distribution of electrical properties of tissues. Up to 3500 full-wave simulations for seven different scenarios are performed. Utilizing parameter prioritization in ANNs enables high accuracy results with fewer input parameters, allowing improved physical interpretability. By applying this method, the required number of numerical simulations (samples) for an optimal dataset is approximately 5 to 10 times the total number of input parameters. The results of this innovative method demonstrate that the reduced dataset successfully encapsulates the core aspects of the SAR problem under investigation, resulting in ML prediction accuracy surpassing 95% while reducing time and memory consumption by approximately 60%.Publicationtype: Journal Article20 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Modeling electrically long interconnects using physics-informed delayed gaussian processes(IEEE, 2023-12-01); ; ; Dhaene, TomThis work presents a machine learning technique to model wide-band scattering parameters (S-parameters) of interconnects in the frequency domain using a new Gaussian processes (GP) model. Standard GPs with a general-purpose kernel typically assume high smoothness and therefore are not suitable to model S-parameters that are highly dynamic and oscillating due to propagation delays. The new delayed Gaussian process (<inline-formula><tex-math notation="LaTeX">$\tau$</tex-math></inline-formula>GP) model employs a physics-informed kernel consisting of periodic components, whose fundamental frequencies are interpreted as tunable propagation delays. Then, the model hyperparameters are tuned using a combination of maximum marginal likelihood estimation (MMLE) and delay estimation using Gabor transform. The delay estimation allows one to automatically identify the optimal fundamental frequencies for the kernel, thus increasing the numerical stability of the hyperparameters tuning process. The resulting delayed Gaussian process model accurately predicts the S-parameter values at desired frequency points in the training interval. Two application examples demonstrate the increased accuracy of the new technique, compared to standard Gaussian processes, vector fitting (VF), and delayed vector fitting (DVF) rational models.Publicationtype: Journal Article17 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Simulating aperture coupling of OAM waves through an infinite PEC plane using EFIE-Part II: Application and interpretationIn this second part of this contribution, the penetration of orbital angular momentum (OAM) waves through apertures is studied at 100 MHz to explore the effects on its behavior. OAM waves can have multiple OAM modes that are orthogonal in free space in terms of excitation and reception. Penetration of these waves through apertures is fundamental to many applications and can cause crosstalk within the OAM wave system and interference in systems beyond the aperture, leading to electromagnetic compatibility (EMC) problems. This article focuses on three aspects of aperture penetration: the influence of aperture shape, changes in the distance behavior of the OAM wave after penetration, and the effect of the OAM wave position and angle of arrival on the aperture. To isolate the effect of an aperture, simulating it in an infinite perfect electrically conducting (PEC) plane is necessary. Therefore, an appropriate algorithm was derived in Part I, where it was also discovered that OAM modes could penetrate apertures differently. Here, this algorithm will be used over 18 000 times to study aperture penetration. Apertures are shown to change the distance behavior of OAM modes. The symmetry of the channel between two arrays influences the crosstalk and can be used to predict the crosstalk.Publicationtype: Journal Article17 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Simulating aperture coupling of OAM waves through an infinite PEC plane using EFIE-MoM - Part I: Validation and numerical accuracy(IEEE, 2023-07-27); ; ; ; In this first part of our contribution on orbital angular momentum (OAM) wave aperture coupling, an algorithm is implemented and validated. This algorithm simulates aperture coupling through an infinite perfect electrically conducting (PEC) plane using an electric field integral equation (EFIE) based method of moments (MoM) tool at 100 MHz. The aim is to better understand crosstalk introduced within OAM mode systems and the ability of OAM modes to penetrate apertures and interfere with systems behind them. This will be investigated in Part II. Simulating OAM waves accurately is challenging because it involves evaluating small modal differences in complex field amplitudes excited by ports. A surface-based MoM solver is well-suited for this application because it requires only a small discretization effort that can be carefully controlled for accuracy and symmetry. The simulation of apertures in an infinite PEC plane requires simulating either the PEC plane, i.e., an infinite object, or, using Babinet's principle, a finite perfectly magnetic conducting (PMC) plane, which is usually easier. Volume-based finite element method (FEM) solver can approximate PMC structures but face accuracy challenges and volume limitations. The presented algorithm exploits the similarities in the scattering of PMC and PEC surfaces in an MoM solver to emulate a simulation of PMC surfaces.Publicationtype: Journal Article18 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , A waveform relaxation solver for transient simulation of large-scale nonlinearly loaded shielding structures(IEEE, 2022-09-22); ; ; ; This article introduces an algorithm for transient simulation of electromagnetic structures loaded by lumped nonlinear devices. The reference application is energy-selective shielding, which adopts clipping devices uniformly spread along shield apertures to achieve a shielding effectiveness that increases with the power of the incident field, thereby blocking high-power interference while allowing low-power communication. Transient simulation of such structures poses a number of challenges, related to their large-scale and low-loss nature. In this work, we propose a waveform relaxation (WR) scheme based on decoupling the linear electromagnetic structure from its nonlinear terminations. In a preprocessing stage, the electromagnetic subsystem is characterized in the frequency domain and converted into a behavioral rational macromodel. Transient simulation is performed by refining estimates of the port signals through iterations. The proposed scheme combines a time partitioning approach with an inexact Newton–Krylov solver. This combination provides fast convergence also in those cases where standard WR schemes fail due to a strong mismatch at the decoupling sections. Numerical results on several test cases of increasing complexity with up to 1024 ports show that the proposed approach proves as reliable as HSPICE in terms of accuracy, with a speedup ranging from one to three orders of magnitude.Publicationtype: Journal Article21 59 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Iteration Dependent Waveform Relaxation for Hybrid Field Nonlinear Circuit Problems(2022-08-01); ; ; ; This article presents a novel waveform relaxation scheme to solve electromagnetically large structures loaded with lumped linear and nonlinear elements. The scheme partitions the problem into a linear electromagnetic structure and a possibly nonlinear lumped circuit, which are coupled using Thévenin interfaces across the steps of an iterative waveform relaxation scheme. The main novel contribution is an adaptive selection of the decoupling resistances used as port references to define incident and reflected scattering signals, whose time-domain samples are refined through iterations. The decoupling resistances are updated through iterations, with the main objective of improving convergence speed and ultimately runtime. The resulting scheme is self-adapting to terminations exploiting high dynamic range in their impedance profiles and is able to provide a suboptimal convergence rate. Three-dimensional shielding structures loaded with nonlinear elements are employed as numerical examples to demonstrate the proposed method.Publicationtype: Journal Article31