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-based control of multilayer electrospinning. The task of the PhD student is constructing a scalable, multiparameter model, which maps online observable process parameters (e.g. spinneret voltage, flow
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Description The aim of this research is to enhance the durability and fire resistance of veneer-based wood products by developing and optimizing a sustainable wood densification process. The study seeks
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focus on developing new power electronics and control architectures to enable the operation of residential HVAC systems (heat pumps and heat recovery ventilation units) in droop-controlled DC microgrids
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model, which maps online observable process parameters (e.g. spinneret voltage, flow rate etc.) to nanofiber product quality (e.g. morphology, diameter variance, all of which are only observable offline
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on the electrical machine optimization to achieve high energy-efficient drive system. The practical part of the work will be testing the control model with a prototype machine in the research laboratory. Research
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process (process-specific design) (2) Optimization of the LPBF process parameters to achieve desired microstructure and material properties, (3) In-depth materials, and property testing and (4) Prototype
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the progress toward the energy balance, enabling PEBs, PEDs, and other Smart City installations. Research plan Collecting and analyzing multimodal data (3D models, point clouds, building metadata, Smart City
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new paradigm in the design, testing, and validation of Electronic Control Units (ECUs) for Connected and Autonomous Vehicles. By developing high-fidelity Digital Twins (DTs) that combine functional
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Japan have initiated the Japanese governmental task to elaborate a Strategy Map for Smart Cities, under the leadership of Professor Takehiko Nagumo. Smart Cities are the currently leading paradigm in
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new paradigm in the validation of autonomous driving software, focusing on the intersection of Large Language Models (LLMs) and Autonomy 2.0 / End-to-End (E2E) approaches. While E2E models promise