Related papers: Machine learning based digital twin for dynamical …
The use of Digital Twins is set to transform the manufacturing sector by aiding monitoring and real-time decision making. For several applications in this sector, the system to be modeled consists of a mix of discrete-event and continuous…
A digital twin is a surrogate model that has the main feature to mirror the original process behavior. Associating the dynamical process with a digital twin model of reduced complexity has the significant advantage to map the dynamics with…
Commonly adopted in the manufacturing and aerospace sectors, digital twin (DT) platforms are increasingly seen as a promising paradigm to control and monitor software-based, "open", communication systems, which play the role of the physical…
Recent technological developments and advances in Artificial Intelligence (AI) have enabled sophisticated capabilities to be a part of Digital Twin (DT), virtually making it possible to introduce automation into all aspects of work…
The digital twin has emerged as a technology to predict the undesirables, and ensure desired performance of complex systems. Although digital twins have got attention in the manufacturing research spectrum, yet their industrial application…
Digital twins are transforming engineering and applied sciences by enabling real-time monitoring, simulation, and predictive analysis of physical systems and processes. However, conventional digital twins rely primarily on passive data…
Prediction of wireless channels and their statistics is a fundamental procedure for ensuring performance guarantees in wireless systems. Statistical radio maps powered by Gaussian processes (GPs) offer flexible, non-parametric frameworks,…
Digital twin (DT) technology enables real-time simulation, prediction, and optimization of physical systems, but practical deployment faces challenges from high data requirements, proprietary data constraints, and limited adaptability to…
Digital Twin was introduced over a decade ago, as an innovative all-encompassing tool, with perceived benefits including real-time monitoring, simulation and forecasting. However, the theoretical framework and practical implementations of…
The development of Digital Twins (DTs) represents a transformative advance for simulating and optimizing complex systems in a controlled digital space. Despite their potential, the challenge of constructing DTs that accurately replicate and…
Digital twins have become popular for their ability to monitor and optimize a process or a machine, ideally through its complete life cycle using simulations and sensor data. In this paper, we focus on the challenge of accurate and…
The design and operation of systems are conventionally viewed as a sequential decision-making process that is informed by data from physical experiments and simulations. However, the integration of these high-dimensional and heterogeneous…
Digital Twins (DTs) are becoming increasingly vital for future industrial applications, enhancing monitoring, control, and optimization of physical assets. This enhancement is made possible by integrating various Digital Models (DMs) within…
Soft robots, made from compliant materials, exhibit complex dynamics due to their flexibility and high degrees of freedom. Controlling soft robots presents significant challenges, particularly underactuation, where the number of inputs is…
Digital Twins (DTs) are virtual representations of physical systems synchronized in real time through Internet of Things (IoT) sensors and computational models. In industrial applications, DTs enable predictive maintenance, fault diagnosis,…
We propose a synthesis method for the design of digital twins applicable to various systems (pneumatic, hydraulic, electrical/electronic circuits). The methodology allows representing the operation of these systems through an active digital…
Digital twins, as precise digital representations of physical systems, have evolved from passive simulation tools into intelligent and autonomous entities through the integration of artificial intelligence technologies. This paper presents…
The accurate and efficient modeling of nuclear reactor transients is crucial for ensuring safe and optimal reactor operation. Traditional physics-based models, while valuable, can be computationally intensive and may not fully capture the…
This paper examines a robust data-driven approach for the safe deployment of systems with nonlinear dynamics using their imperfect digital twins. Our contribution involves proposing a method that fuses the digital twin's nominal trajectory…
This work shows how adaptivity can enhance value realization of digital twins in civil engineering. We focus on adapting the state transition models within digital twins represented through probabilistic graphical models. The bi-directional…