Uncertainty quantification for SAE J2954 compliant static wireless charge components

V Cirimele, R Torchio, JL Villa, F Freschi, P Alotto… - IEEE …, 2020 - ieeexplore.ieee.org
The present work aims at quantifying how, and how much, the uncertainties on the
components and material parameters of a wireless power transfer (WPT) system for the …

Challenges in the electromagnetic modeling of road embedded wireless power transfer

V Cirimele, R Torchio, A Virgillito, F Freschi, P Alotto - Energies, 2019 - mdpi.com
In this paper, starting from the experimental experience of the road embedment of a
transmitting coil for wireless power transfer, a numerical model of such device is constructed …

[PDF][PDF] 基于均值点展开的单变元降维法在EIT 不确定性量化研究中的应用

赵营鸽, 李颖, 王灵月, 崔阳阳… - TRANSACTIONS OF …, 2021 - dgjsxb.ces-transaction.com
摘要在电阻抗成像(EIT) 技术中, 介质参数的不确定性会对正问题计算产生影响,
进而影响图像重构, 因而, 对EIT 介质参数不确定性量化的研究具有重要的意义 …

A Polynomial Chaos Expansion Approach to Interval Estimation for Uncertain Fuzzy Systems

Z Wang, L Zhang, CK Ahn… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In this article, we propose a polynomial chaos expansion (PCE) approach to interval
estimation for uncertain Takagi–Sugeno fuzzy systems by considering time-invariant …

Uncertainty Quantification in PEEC Method: A Physics-Informed Neural Networks-Based Polynomial Chaos Expansion

Y Ping, Y Zhang, L Jiang - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In this article, we propose a novel machine learning approach for uncertainty quantification
(UQ) within the partial equivalent element circuit (PEEC) framework, employing physics …

Fast uncertainty quantification in low frequency electromagnetic problems by an integral equation method based on hierarchical matrix compression

R Torchio, L Codecasa, L Di Rienzo, F Moro - IEEE Access, 2019 - ieeexplore.ieee.org
A parametric model order reduction method combined with a polynomial spectral
approximation is applied for the first time to a Volume Integral Equation method accelerated …

High-Dimensional Uncertainty Quantification in Electrical Impedance Tomography Forward Problem Based on Deep Neural Network

Y Zhao, L Wang, Y Li, R He, C Ma - IEEE Access, 2023 - ieeexplore.ieee.org
In electrical impedance tomography (EIT), the uncertainty of conductivity distribution may
cause the uncertainty in the forward calculation and further affect the inverse problem. In this …

Extending the unstructured PEEC method to magnetic, transient, and stochastic electromagnetic problems

R Torchio - 2019 - theses.hal.science
The main focus of this thesis is to extend and improve the applicability and the accuracy of
the Unstructured Partial Element Equivalent Circuit (PEEC) method. The interest on this …

An Improved Multi-dimensional Uncertainty Quantification Method Based on DNN-DRM

Y Zhao, L Wang, Y Li, R Jin… - Journal of Physics …, 2023 - iopscience.iop.org
Mathematical modeling is a method that uses mathematical methods to solve problems in
real life. In the process of modeling, the inherent properties of the parameters and the …

[PDF][PDF] МОДЕЛИРОВАНИЕ РУДНИЧНОГО ДВИГАТЕЛЯ ПОСРЕДСТВОМ РЕШЕТЧАТОЙ СХЕМЫ ЗАМЕЩЕНИЯ С СИНУСОИДАЛЬНЫМИ ИСТОЧНИКАМИ ТОКА

АВ Бланк - 2022 - giab-online.ru
в горной промышленности широкое применение находят электрические машины (в
том числе—и асинхронные двигатели), которые, как правило, работают в очень …