Related papers: Digital twin-based hybrid framework for steam gene…
Reliable forecasting is critical for early warning systems and adaptive drought management. Most previous deep learning approaches focus solely on homogeneous regions and rely on single-structured data. This paper presents a hybrid neural…
The use of machine learning (ML) model as digital-twins for reduced-order-modeling (ROM) in lieu of system codes has grown traction over the past few years. However, due to the complex and non-linear nature of nuclear reactor transients as…
As the integration of digital technologies and communication systems continues within distribution grids, new avenues emerge to tackle energy transition challenges. Nevertheless, this deeper technological immersion amplifies the necessity…
This paper presents a novel methodological framework, called the Actor-Simulator, that incorporates the calibration of digital twins into model-based reinforcement learning for more effective control of stochastic systems with complex…
We investigate the influence of microstructural traps on hydrogen diffusion and embrittlement in the presence of cyclic loads. A mechanistic, multi-trap model for hydrogen transport is developed, implemented into a finite element framework,…
Coastal communities are confronted with a growing incidence of climate-induced flooding, necessitating adaptation measures for resilience. In this paper, we introduce a framework that integrates an urban digital twin with a geospatial…
In this work, a numerical simulation framework is presented based on the Phase Field Method that is able to capture the evolution of heterogeneous metallic microstructures during solidification. The involved physics can prove especially…
In the electrical grid, the distribution system is themost vulnerable to severe weather events. Well-placed and coordinatedupgrades, such as the combination of microgrids, systemhardening and additional line redundancy, can greatly reduce…
This paper has proposed an easily replicable and novel approach for developing a Digital Twin (DT) system for industrial robots in intelligent manufacturing applications. Our framework enables effective communication via Robot Web Service…
Wind turbine is a complex machine with its rotating and non-rotating equipment being sensitive to faults. Due to increased wear and tear, the maintenance aspect of a wind turbine is of critical importance. Unexpected failure of wind turbine…
Future communication networks are expected to achieve deep integration of communication, sensing, and computation, forming a tightly coupled and autonomously operating infrastructure system. However, current reliance on centralized control,…
In this paper, we introduce a decentralized digital twin (DDT) framework for dynamical systems and discuss the prospects of the DDT modeling paradigm in computational science and engineering applications. The DDT approach is built on a…
Digital Twins are digital replica of real entities and are becoming fundamental tools to monitor and control the status of entities, predict their future evolutions, and simulate alternative scenarios to understand the impact of changes.…
Although the emergence of 6G IoT networks has accelerated the deployment of enhanced smart city services, the resource limitations of IoT devices remain as a significant problem. Given this limitation, meeting the low-latency service…
This paper introduces a novel strategy aimed at enhancing productivity and minimizing non-productive movements within container terminals, specifically focusing on container yards. It advocates for the implementation of a digital twin-based…
We investigate how clogging affects the transfer properties of a generic class of materials featuring a hydraulic network embedded in a matrix. We consider the flow of a liquid through fully saturated hydraulic networks which transfer heat…
This paper proposes online algorithms for dynamic matching markets in power distribution systems, which at any real-time operation instance decides about matching -- or delaying the supply of -- flexible loads with available renewable…
Electrification of residential heating and transporta- tion has the potential to overload transformers in distribution feeders. Strategic scheduling of transformer upgrades to antici- pate increasing loads can avoid operational failures and…
Robots are unrelentingly used to achieve operational efficiency in Industry 4.0 along with symbiotic and sustainable assistance for the work-force in Industry 5.0. As resilience, robustness, and well-being are required in anti-fragile…
This paper explores the conditions under which global contraction manifests in the leaky continuous time reservoirs, thus guaranteeing generalized synchronization. Results on continuous time reservoirs make use of the logarithmic norm of…