Henrik Asmuth
Researcher at Uppsala University
Based in Bremen, Germany
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Seniority
Staff
Department
Science
Location
Bremen
Industry
Higher Education
Company size
10K
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h•••••••@uu.se
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Background
About Henrik Asmuth
The large scale expansion of wind power confronts us with various modelling challenges. My research focusses on the development of more efficient and more accurate modelling tools for wind energy and atmospheric applications. This includes both numerical (large-eddy simulation and lattice Boltzmann Methods) and data-driven methods (e.g. using deep convolutional neural networks) as well as combined approaches. Regardless of the approach, I am leveraging GPUs in order to maximise the computational efficiency. Throughout many international research projects I have been involved in modelling tasks in the fields of wind farm control (combining large-eddy simulation and reinforcement learning), validations of engineering models, and wind turbine icing. Key skills: Numerical modelling, deep learning, surrogate models, fluid dynamics, C++, CUDA, python
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