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failure analysis using advanced finite element models and simulation techniques. This is enabled by digital and sensor technologies such as artificial intelligence, computer vision, drones, and robotics
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Foundation Classes (IFC), and linked data Sensors as part of Internet of Things (IoT) and integration of sensory information in simulation models during run-time Data processing, incl. artificial intelligence
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are developed, modelled and controlled. You will create novel adaptative, physics-informed models that tightly integrate thermo-fluid dynamic laws, deep learning neural networks, and experimental data. A key
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linked data Sensors as part of Internet of Things (IoT) and integration of sensory information in simulation models as part of Digital Building Twins (DBT) during run-time Life cycle and sustainability
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mathematical and analytical models to predict coil loss, facilitating the optimal design of HPMCs Constructing a large-signal platform to measure coil loss of HPMCs Exploring innovative solutions, such as new
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simulation techniques and molecular mechanics principles (especially applied on water and hydrogen bonding systems). Thermodynamic modeling and applied physical chemistry for industrial applications. As a
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development of our hybrid power plant simulation models and controllers, mainly the plant level controllers taking into account the interaction with commercial wind turbine, PV systems, battery system and their
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research assistants, postdoctoral researchers, and academic staff to develop cutting-edge methodologies. The research is cross-disciplinary, combining advanced quantitative analysis, simulation, and systems
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simulation/theory of 2D materials and devices, within electronics, photonics and mass transport. Biophysics and Fluids with a focus on fluid and soft-matter dynamics on small length scales, often with life