A5060572659- Digital Transformation in Industry
- Offshore Engineering and Technologies
- Technology Assessment and Management
- Energy Load and Power Forecasting
- Arctic and Russian Policy Studies
- Social Acceptance of Renewable Energy
- Cosmology and Gravitation Theories
- Maritime Transport Emissions and Efficiency
- Dark Matter and Cosmic Phenomena
- Oil and Gas Production Techniques
- Privacy-Preserving Technologies in Data
- IoT and Edge/Fog Computing
- Reservoir Engineering and Simulation Methods
- Wind and Air Flow Studies
- Low-power high-performance VLSI design
- Advanced Vision and Imaging
- Augmented Reality Applications
- Additive Manufacturing Materials and Processes
- Computational Physics and Python Applications
- Galaxies: Formation, Evolution, Phenomena
- Engineering Education and Technology
- Wind Energy Research and Development
- Environmental Impact and Sustainability
- Advanced Neural Network Applications
- Image and Signal Denoising Methods
Norwegian University of Science and Technology
2023-2024
RWTH Aachen University
2022
This article presents a comprehensive overview of the digital twin technology and its capability levels, with specific focus on applications in wind energy industry. It consolidates definitions levels scale from 0-5; 0-standalone, 1-descriptive, 2-diagnostic, 3-predictive, 4-prescriptive, 5-autonomous. then, an industrial perspective, identifies current state art research needs sector. is concluded that main challenges hindering realization highly capable twins fall into one four categories;...
Abstract In modern analysis pipelines, Einstein-Boltzmann Solvers (EBSs) are an invaluable tool for obtaining CMB and matter power spectra. To significantly accelerate the computation of these observables, CosmicNet strategy is to replace usual bottleneck EBS, which integration a system differential equations linear cosmological perturbations, by trained neural networks. This offers several advantages compared direct emulation final including very small networks that easy train in...
Abstract Digital Twins bring several benefits for planning, operation, and maintenance of remote offshore assets. In this work, we explain the digital twin concept capability level scale in context wind energy. Furthermore, demonstrate a standalone twin, descriptive prescriptive an operational floating turbine. The consists virtual representation turbine its operating environment. While at does not evolve with physical turbine, it can be used during planning-, design-, construction phases....
Abstract In this work, a digital twin with standalone, descriptive, and predictive capabilities is created for an existing onshore wind farm located in complex terrain. A standalone implemented virtual-reality-enabled 3D interface using openly available data on the turbines their environment. Real SCADA from are being used to elevate descriptive level. The complemented weather forecasts microscale model nested into Scandinavian meteorological forecasts, resources visualized inside...
Abstract The demand for condition-based and predictive maintenance is rising across industries, especially remote, high-value, high-risk assets. In this article, the diagnostic digital twin concept introduced, discussed, implemented a floating offshore turbine. A virtual representation of an asset that combines real-time data models to monitor damage, detect anomalies, diagnose failures, thereby enabling maintenance. By applying twins assets, unexpected failures can be alleviated, but...
Digital twins are becoming increasingly popular across many industries for real-time data streaming, processing, and visualization. They allow stakeholders to monitor, diagnose, optimize assets. Emerging technologies used immersive visualization, such as virtual reality, open new possibilities intuitive access monitoring of remote assets through digital twins. This is specifically relevant floating wind farms, where often limited. However, the integration from multiple sources different...
NorthWind, a collaborative research initiative supported by the Research Council of Norway, industry stakeholders, and partners, aims to advance cutting-edge innovation in wind energy. The core mission is reduce power costs foster sustainable growth, with key focus on development digital twins. A twin virtual representation physical assets or processes that uses data simulators enable real-time forecasting, optimization, monitoring, control informed decision-making. Recently, hierarchical...
The demand for condition-based and predictive maintenance is rising across industries, especially remote, high-value, high-risk assets. In this article, the diagnostic digital twin concept introduced, discussed, implemented a floating offshore turbine. A virtual representation of an asset that combines real-time data models to monitor damage, detect anomalies, diagnose failures, thereby enabling maintenance. By applying twins assets, unexpected failures can be alleviated, but implementation...
Abstract Real-time capable models are paramount for the successful adaptation of digital twin technology into industries such as wind energy, but high-fidelity physics-based cannot achieve required speed, while data-driven and hybrid methods require large amounts training data which is typically confidential. In this work, combination federated learning with modeling proposed to train fast reliable across multiple confidential sets owned by different stakeholders. The approach demonstrated...
Abstract NorthWind, a collaborative research initiative supported by the Research Council of Norway, industry stakeholders, and partners, aims to advance cutting-edge innovation in wind energy. The core mission is reduce power costs foster sustainable growth, with key focus on development digital twins. A twin virtual representation physical assets or processes that uses data simulators enable real-time forecasting, optimization, monitoring, control informed decision-making. Recently,...
This paper explores the development and practical application of a predictive digital twin specifically designed for condition monitoring, using advanced mathematical models thermal imaging techniques. Our work presents comprehensive approach to integrating Proper Orthogonal Decomposition (POD), Robust Principal Component Analysis (RPCA), Dynamic Mode (DMD) establish robust framework. We employ these methods in real-time experimental setup involving heated plate monitored through imaging....
In modern analysis pipelines, Einstein-Boltzmann Solvers (EBSs) are an invaluable tool for obtaining CMB and matter power spectra. To accelerate the computation of these observables, CosmicNet strategy is to replace bottleneck EBS, which integration a system differential equations linear cosmological perturbations, by neural networks. This offers advantages compared direct emulation final including small networks that easy train in high-dimensional parameter spaces, do not depend on...
Digital Twins bring several benefits for planning, operation, and maintenance of remote offshore assets. In this work, we explain the digital twin concept capability level scale in context wind energy. Furthermore, demonstrate a standalone twin, descriptive prescriptive an operational floating turbine. The consists virtual representation turbine its operating environment. While at does not evolve with physical turbine, it can be used during planning-, design-, construction phases. At next...
In this work, a digital twin with standalone, descriptive, and predictive capabilities is created for an existing onshore wind farm located in complex terrain. A standalone implemented virtual-reality-enabled 3D interface using openly available data on the turbines their environment. Real SCADA from are used to elevate descriptive level. The complemented weather forecasts microscale model nested into Scandinavian meteorological forecasts, resources visualized inside human-machine interface....
Atmospheric flows are governed by a broad variety of spatio-temporal scales, thus making real-time numerical modeling such turbulent in complex terrain at high resolution computationally intractable. In this study, we demonstrate neural network approach motivated Enhanced Super-Resolution Generative Adversarial Networks to upscale low-resolution wind fields generate high-resolution an actual farm Bessaker, Norway. The network-based model is shown successfully reconstruct fully resolved 3D...
Digital twins are becoming increasingly popular across many industries for real-time data streaming, processing, and visualization. They allow stakeholders to monitor, diagnose, optimize assets. Emerging technologies used immersive visualization, such as virtual reality, open new possibilities intuitive access monitoring of remote assets through digital twins. This is specifically relevant floating wind farms, where often limited. However, the integration from multiple sources different...