Modeling of the Maximum Induced Currents in Automotive Radiated Immunity Tests via Thevenin-based Metamodels

This paper presents three different metamodels for the prediction of the maximum current induced on key vehicle electronic units during an automotive radiated immunity test. The proposed modeling approach is based on a Thevenin circuital interpretation of the test setup which is estimated from a small set of measurements or simulations. The FFT-based trigonometric regression, the support vector machine and the Gaussian process regression are then applied to provide three different metamodels able of predicting the spectrum of the induced currents for any value of the incidence angle of the external EM field. The accuracy and the convergence of the proposed alternatives are investigated by comparing model predictions with the results obtained by means of a parametric full-wave electromagnetic simulation

Worst-Case Optimization of a Digital Link for Wearable Electronics in a Stochastic Framework

This paper demonstrates an optimization strategy for systems affected by uncertainties in the case of a textile interconnect line. Rather than simply conducting stochastic analysis at the end of the design process, tolerances are accounted for from the early stages of the flow. An unsupervised approach, used to describe the stochastic behavior of the line, isintegrated within a heuristic optimization algorithm with the aim of selecting the optimal parameters of a passive equalizer

Comparison of Stochastic Methods for the Variability Assessment of Technology Parameters

This paper provides and compares two alternative solutions for the simulation of cables and interconnects with the inclusion of the effects of parameter uncertainties, namely the Polynomial Chaos (PC) method and the Response Surface Modeling (RSM). The problem formulation applies to the telegraphers equations with stochastic coefficients. According to PC, the solution requires an expansion of the unknown parameters in terms of orthogonal polynomials of random variables. On the contrary, RSM is based on a least-square polynomial fitting of the system response. The proposed methods offer accuracy and improved efficiency in computing the parameter variability effects on system responses with respect to the conventional Monte Carlo approach. These approaches are validated by means of the application to the stochastic analysis of a commercial multiconductor flat cable. This analysis allows us to highlight the respective advantages and disadvantages of the presented method

Topological modelling of gas networks for co-simulation applications in multi-energy systems

This paper focuses on the modelling and simulation of gas networks to be used in an integrated multi-carrier energy scenario. A topological approach is followed, where a simplified graph-based description of the gas network is adopted and a systematic analysis of the metrics of three real test cases is carried out with the aim of discovering relevant network features. The governing equations of the basic building blocks such as pipelines, compressors and pressure reduction stations are readily derived under the assumptions of steady-state operation and isothermal behaviour, allowing a good matching between model compactness and accuracy. In addition, a circuit-based interpretation of model equations and well-established tools for circuit analysis are used. The obtained results proved that the proposed approach offers a feasible tool for gas networks, which can be readily integrated in a co-simulation framework

How Online Solutions Help Beat the Lockdown in Higher Education: A Central Asia Case Study

This chapter is aimed at summarizing the recent initiatives put in action for solving the problems in delivering the educational services in the Turin Polytechnic University in Tashkent, TTPU, after the lockdown, and the stringent measures taken by the Uzbek government in March 2020, for the pandemic explosion of the COVID-19 virus. The long-lasting connection between Politecnico di Torino, a European University, and this Central Asia Institution has been proven to be extremely effective, maximizing the benefits of TTPU in promptly offering online solutions for remote lectures, and the preparation of the technical substrate for both the exams and admission test which will be delivered after the completion of the second semester lectures. A summary of the IT tools adopted, with compact highlights of their features, as well as the qualitative feedback collected from the first courses offered with a reshaped structure suitable for online classes are thoroughly discussed in this work

Machine learning for the performance assessment of high-speed links

This paper investigates the application of support vector machine to the modeling of high-speed interconnects with largely varying and/or highly uncertain design parameters. The proposed method relies on a robust and well-established mathematical framework, yielding accurate surrogates of complex dynamical systems. An identification procedure based on the observation of a small set of system responses allows generating compact parametric relations, which can be used for design optimization and/or stochastic analysis. The feasibility and strength of the method are demonstrated based on a benchmark function and on the statistical assessment of a realistic printed circuit board interconnect, highlighting the main features and benefits of this technique over state-of-the-art solutions. Emphasis is given to the effects of the initial sample size and of input noise on the model estimation

Topological modelling and simulation of gas networks for multi-energy applications

This paper addresses the generation of a topological model of a gas network to be used in an integrated multi-carrier energy co-simulation framework. The study is based on a set of three real gas networks and emphasis is put on both a unified graph based description and a steady-state simulation carried out via an electrical circuit analogy and classical tools for circuit analysis. An isothermal assumption is also considered and validated. The proposed approach turns out to be a first step toward a simple and viable solution for the efficient co- simulation of a possibly complex energy scenario involving renewables, electrical and gas networks

A Compact Detector for Flexible Partial Discharge Monitoring of 10-kV Overhead Covered Conductor Lines

The availability of accurate and cost-effective solutions for the real-time monitoring of overhead covered conductors (CC) is now becoming an important tool for the reliability and condition assessments of this class of electrical lines. This is even more crucial due to the possibly large number of conductors and the wide geographical spread of the electrical network. This letter proposes a smart and compact detector for partial discharge (PD) based monitoring, matching the above needs and offering a flexible and cost-effective solution with some important features, including a non-invasive sensing, a field energy harvesting function, and a low-power working operation. The detector has been designed and implemented, proving its effectiveness on real cases involving PD-affected 10 kV CC lines