Related papers: Active Digital Twins via Active Inference
Digital twin (DT) is one of the most promising enabling technologies for realizing smart grids. Characterized by seamless and active---data-driven, real-time, and closed-loop---integration between digital and physical spaces, a DT is much…
Digital twin (DT) technologies have emerged as a solution for real-time data-driven modeling of cyber physical systems (CPS) using the vast amount of data available by Internet of Things (IoT) networks. In this position paper, we elucidate…
Industrial process optimization and control is crucial to increase economic and ecologic efficiency. However, data sovereignty, differing goals, or the required expert knowledge for implementation impede holistic implementation. Further,…
As telecommunications networks become increasingly complex, the integration of advanced technologies such as network digital twins and generative artificial intelligence (AI) emerges as a pivotal solution to enhance network operations and…
We introduce a novel digital twin framework for predictive maintenance of long-term physical systems. Using monitoring tire health as an application, we show how the digital twin framework can be used to enhance automotive safety and…
We articulate the design imperatives for machine-learning based digital twins for nonlinear dynamical systems subject to external driving, which can be used to monitor the ``health'' of the target system and anticipate its future collapse.…
This paper presents a proof-of-concept digital twin framework for simulation-driven diabetes modeling using benchmark clinical data, synthetic temporal augmentation, and illustrative continuous glucose monitoring (CGM) analysis. Unlike…
Active inference is a mathematical framework which originated in computational neuroscience as a theory of how the brain implements action, perception and learning. Recently, it has been shown to be a promising approach to the problems of…
Animal behavior reflects interactions between the nervous system, body, and environment. Therefore, biomechanics and environmental context must be considered to understand algorithms for behavioral control. Neuromechanical digital twins,…
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…
Digital twinning in structural engineering is a rapidly evolving technology that aims to eliminate the gap between physical systems and their digital models through real-time sensing, visualization, and control techniques. Although Digital…
The evolution of network virtualization and native artificial intelligence (AI) paradigms have conceptualized the vision of future wireless networks as a comprehensive entity operating in whole over a digital platform, with smart…
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 twin technology has a huge potential for widespread applications in different industrial sectors such as infrastructure, aerospace, and automotive. However, practical adoptions of this technology have been slower, mainly due to a…
As the real-time digital counterpart of a physical system or process, digital twins are utilized for system simulation and optimization. Neural networks are one way to build a digital twins model by using data especially when a…
Commonly adopted in the manufacturing and aerospace sectors, digital twin (DT) platforms are increasingly seen as a promising paradigm to control, monitor, and analyze software-based, "open", communication systems. Notably, DT platforms…
Central to the digital transformation of the process industry are Digital Twins (DTs), virtual replicas of physical manufacturing systems that combine sensor data with sophisticated data-based or physics-based models, or a combination…
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 cybernetics, data processing and management tools bring the…
Digital twins promise to revolutionize engineering by offering new avenues for optimization, control, and predictive maintenance. We propose a novel framework for simultaneously training the digital twin of an engineering system and an…
The potential of digital twin technology is yet to be fully realized due to its diversity and untapped potential. Digital twins enable systems' analysis, design, optimization, and evolution to be performed digitally or in conjunction with a…