Digital twins, which are considered an effective approach to realize the fusion between
virtual and physical spaces, have attracted a substantial amount of attention in the past …

By interacting, synchronizing, and cooperating with its physical counterpart in real time,
digital twin (DT) is promised to promote an intelligent, predictive, and optimized modern city …

With the rapid development of industrial digitalization and intelligence, there is an urgent
need to accurately depict the physical world in digital space, and, in turn, regulate and …

The flexible operation of coal-fired boilers deteriorates the heat transfer capacity of tubes,
leading to localized overheating, tube cracking, and even boiler failure. This study presents …

Recent digital advances have popularized predictive maintenance (PMx), offering enhanced
efficiency, automation, accuracy, cost savings, and independence in maintenance …

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 …

In Industry 4.0, the digital twin is one of the emerging technologies, offering simulation
abilities to predict, refine, and interpret conditions and operations, where it is crucial to …

We propose a novel framework for discovering Stochastic Partial Differential Equations
(SPDEs) from data. The proposed approach combines the concepts of stochastic calculus …

The discovery of partial differential equations (PDEs) is a challenging task that involves both
theoretical and empirical methods. Machine learning approaches have been developed and …

We introduce a novel digital twin framework for predictive maintenance of physical systems
with long term operations. Using monitoring tire health as an application, we show how the …