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technologies based on a digital twin. The digital twin will combine information from the physical structure with models and monitoring data to assess its current structural state and predict its remaining
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the performance of the welded interface. Implement the developed models in commercial FE simulation software for the development of a digital twin and validate their accuracy against experiments. We are looking
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will be employed and tested on actual measurement data as a benchmark. The project will involve mathematical modeling, construction of numerical methods, coding, testing, numerical simulations, and
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scientific knowledge, such as physical laws, differential equations, and domain-specific constraints, to model, simulate, and understand complex systems. The project will explore modern SciML methods
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increasingly popular in recent years. The recent introduction of OpenAI’s ChatGPT made large-scale models available to the public, which enables the integration of AI in everyday objects and tasks. As a result
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design rules to understand their chemistry and physics. You will combine coarse-grained and atomistic simulations with surrogate models and experimental insights (with Dr. Baumgartner) to understand
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-resolved simulations. In case a fluidized bed is chosen, a traditional Eulerian Two-Fluid model (TFM) will be compared with a novel Lagrangian Continuous Particle Model (CPM). Initially, engineering
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different scenarios; implement and validate simulation models for system analysis, scenario evaluation, and future optimization; collaborateclosely with researchers, industrial partners, and fellow PhD
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of: electromagnetic sensor design, modelling, prototyping and experimental validation. The best fit is A candidate interested in high-frequency measurement techniques, sensor hardware development and precision
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material models, the development of Digital Twins, and the use of AI-based methods. This includes building model-ready databases, developing simulation chains that link process simulations with analysis