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Lightning-Induced Voltage on an Overhead Transmission Line Terminated with Non-veritical Risers

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Field-to-transmission line coupling models

Farhad Rachidi-Haeri, Marcos Rubinstein, Carlo Alberto Nucci

This chapter presents the coupling of lightning electromagnetic fields to overhead and underground lines based on the transmission line approximation. The chapter starts with an introductory section in which the advantages and the drawbacks of three approa ...

IET2020

A Simple And Scalable Technology For Micro And Nano-Topographic Patterning Of Standard Cell Cultureware To Screen Cell Behaviour In Vitro

Jürgen Brugger

MARY ANN LIEBERT, INC2022

Impedance and Admittance Formulas for a Multistair Model of Transmission Towers

Farhad Rachidi-Haeri

This article discusses formulas for the surge/ characteristic impedance of vertical conductors. Calculated results of the surge impedance are compared with measured results on vertical conductors and transmission towers. The accuracy of the available time- ...

2020

VIO-UWB-Based Collaborative Localization and Dense Scene Reconstruction within Heterogeneous Multi-Robot Systems

Fabrizio Schiano

Effective collaboration in multi-robot systems requires accurate and robust estimation of relative localization: from cooperative manipulation to collaborative sensing, and including cooperative exploration or cooperative transportation. This paper introdu ...

IEEE2022

On the representation of thin wires inside lossy dielectric materials for FDTD‐based LEMP simulations

Farhad Rachidi-Haeri, Marcos Rubinstein, Akiyoshi Tatematsu

The finite-difference time-domain method is one of the most widely used numerical electromagnetic computation techniques, and it has become an effective tool for analyzing electromagnetic transient phenomena in three-dimensional structures and grounding sy ...

2019

Deep MinCut: Learning Node Embeddings by Detecting Communities

Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Chi Thang Duong

We present Deep MinCut (DMC), an unsupervised approach to learn node embeddings for graph -structured data. It derives node representations based on their membership in communities. As such, the embeddings directly provide insights into the graph structure ...

ELSEVIER SCI LTD2022

Estimation of the expected annual number of flashovers in power distribution lines due to negative and positive lightning

Farhad Rachidi-Haeri, Carlo Alberto Nucci

The paper deals with the estimation of the expected annual number of flashovers in overhead power distribution lines due to indirect lightning strokes and aims at extending a procedure previously proposed by the authors, limited to negative downward events ...

Elsevier2019

Probabilistic Data Association for Semantic SLAM at Scale

Tony Alan Wood

With advances in image processing and machine learning, it is now feasible to incorporate semantic information into the problem of simultaneous localisation and mapping (SLAM). Previously, SLAM was carried out using lower level geometric features (points, ...

IEEE2022

The Propagation Effects of Lightning Electromagnetic Fields Over Mountainous Terrain in the Earth-Ionosphere Waveguide

Farhad Rachidi-Haeri, Marcos Rubinstein, Mohammad Azadifar

In this paper, a full-wave two-dimensional Finite-Difference-Time-Domain model is developed to evaluate the propagation effects of lightning electromagnetic fields over mountainous terrain in the Earth-ionosphere waveguide. In the model, we investigate the ...

2019

Motivating Children to Practice Perspective-Taking Through Playing Games with Cozmo

Pierre Dillenbourg

Recent studies with children have pointed out the importance of spatial thinking as an essential factor in determining later success in STEM-related fields. The current study explores the potential of using embodied activities with robots to aid the develo ...

IEEE2022

Properties of Direct-Time and Reversed-Time Transfer Functions to Locate Disturbances along Power Transmission Lines

Mario Paolone, Zhaoyang Wang

The paper discusses specific frequency-domain properties of the electromagnetic time reversal (EMTR) method applied to locate faults and, more in general, disturbances in power networks. Specifically, we investigate the properties of two transfer functions ...

IEEE2019

State-of-the-art of data collection, analytics, and future needs of transmission utilities worldwide to account for the continuous growth of sensing data

Mario Paolone

Nowadays, transmission system operators require higher degree of observability in real-time to gain situational awareness and improve the decision-making process to guarantee a safe and reliable operation. Digitalization of energy systems allows utilities ...

ELSEVIER SCI LTD2022

On the Influence of an Elevated Terrain on the Grounding Resistance of a Vertical Rod

Marcos Rubinstein, Antonio Sunjerga

In this paper, we analyze the grounding resistance of a vertical grounding rod located in an elevated terrain. Tall structures such as wind turbines and mobile phone base stations are often installed in remote and hilly locations to gain more power or to f ...

2019

Experimental data-driven model predictive control of a hospital HVAC system during regular use

Colin Neil Jones, Christophe Salzmann, Emilio Maddalena

Herein we report a multi-zone, heating, ventilation and air-conditioning (HVAC) control case study of an industrial plant responsible for cooling a hospital surgery center. The adopted approach to guaranteeing thermal comfort and reducing electrical energy ...

2022

EM Fields Generated by a Scale Model Helical Antenna and Its Use in Validating a Code for Lightning-Induced Voltage Calculation

Farhad Rachidi-Haeri

This paper aims at validating a code for the evaluation of lightning-induced overvoltages developed in the PSCADEMTDC environment using experimental results obtained on an experimental facility deployed at the University of S˜ao Paulo, Brazil that emulates ...

2019

SafeAMC: Adversarial training for robust modulation classification models

Pascal Frossard, Javier Alejandro Maroto Morales

In communication systems, there are many tasks, like modulation classification, for which Deep Neural Networks (DNNs) have obtained promising performance. However, these models have been shown to be susceptible to adversarial perturbations, namely impercep ...

IEEE2022

Tower and Path-Dependent Voltage Effects on the Measurement of Grounding Impedance for Lightning Studies

Marcos Rubinstein, Antonio Sunjerga, Hamidreza Karami, Keyhan Sheshyekani

We present an analysis aimed at evaluating the effect of the presence of the tower on the measurement of the grounding impedance. The Numerical Electromagnetics Code NEC-4 is used for the full-wave modeling of the structure including the tower and its foot ...

2019