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 …

This paper proposes a supervised machine learning framework for the non-intrusive model
order reduction of unsteady fluid flows to provide accurate predictions of non-stationary state …

We put forth a data-driven closure modeling approach for stabilizing projection based
reduced order models for the Bousinessq equations. The effect of discarded modes is taken …

Рассматриваются базовые технологии построения и сопровождения цифровых
двойников (ЦД) с учетом широкого разнообразия задач автоматизации …

This article presents error bounds for a velocity–pressure segregated POD reduced order
model discretization of the Navier–Stokes equations. The stability is proven in L∞(L 2) and …

Approximating solutions of non-linear parametrized physical problems by interpolation
presents a major challenge in terms of accuracy. In fact, pointwise interpolation of such …

This letter is concerned with real-time background flow field estimation using distributed
pressure sensor measurements for autonomous underwater vehicles (AUVs). The goal of …

Preview measurements of the inflow by turbine-mounted lidar systems can be used to
optimise wind turbine performance or alleviate structural loads. However, nacelle-mounted …