Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …

A digital twin can be defined as an adaptive model of a complex physical system. Recent
advances in computational pipelines, multiphysics solvers, artificial intelligence, big data …

This paper presents a literature review on methods for enabling real-time analysis in digital
twins, which are virtual models of physical systems. The advantages of digital twins are …

We describe a fluctuating volume-current formulation of electromagnetic fluctuations that
extends our recent work on heat exchange and Casimir interactions between arbitrarily …

In this paper we propose local approximation spaces for localized model order reduction
procedures such as domain decomposition and multiscale methods. Those spaces are …

We derive fundamental per-channel bounds on angle-integrated absorption and thermal
radiation for arbitrarily structured bodies—for any given material susceptibility and bounding …

A fast frequency domain full-wave electromagnetic simulation method is introduced for the
analysis of MRI coils loaded with the realistic human body models. The approach is based …

Objective: In this paper, we introduce global Maxwell tomography (GMT), a novel volumetric
technique that estimates electric conductivity and permittivity by solving an inverse scattering …

Efficient error estimation is important for reliable reduced-order modeling with guaranteed
accuracy. We propose an error estimator for reduced-order modeling of linear parametric …

We propose a probabilistic way for reducing the cost of classical projection-based model
order reduction methods for parameter-dependent linear equations. A reduced order model …