We are pleased to share that the German and Austrian research agencies DFG and FWF have jointly approved the second funding period of the Collaborative
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Category: MSOEE
Darmstadt. Enhancing AMR Performance with Optimized PM Assembly
This post discusses recent advances in the collaborative project “OptiMag“, carried out between Magnotherm Solutions GmbH and TU Darmstadt.
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Darmstadt. Scalable Algorithms for 3D Simulation of Electric Machines
Prototyping of electrical machines in 3D is becoming increasingly important. It offers more design options for optimization. It also allows the simulation of more complex
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Darmstadt. Machine Learning for Scattering Problems
Designing complex engineering systems often relies on simulation and optimization. Examples include electric motors or high-frequency devices. These processes are based on the Finite Element
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Darmstadt. Advancing Electric Motor Design through novel Optimisation Techniques
Electric machines are a key technology for energy conversion and decarbonisation of the electric grid. This emphasizes the importance of simulation and optimization tools for
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Darmstadt. Low-Frequency Stability in Electroquasistatic Simulations
In the industrial design process of high-voltage equipment, the simulation of electroquasistatic problems is frequently applied. One example of such a case are insulators (see
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Darmstadt. Multiphysical Simulation and Optimisation for Magnetocaloric Refrigeration
Refrigeration has a remarkable and often underestimated impact on global warming: globally, about 20% of the total electric energy is used for refrigeration. Additionally, conventional
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Darmstadt. Towards a Computational Electric Machine Laboratory
TU Darmstadt, TU Graz, JKU Linz and RICAM (ÖAW) collaborate in the first German-Austrian Collaborative Research Centre/Transregio CREATOR – Computational Electrical Machine Laboratory (TRR361/F90). It is funded
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Shape Optimization of an Electron Gun
S-DALINAC (Superconducting-DArmstadt-LINear-ACcelerator) is a superconducting electron accelerator at TU Darmstadt, running since 1991. It was initially constructed as a twice-recirculating accelerator with a maximum energy
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Yield Estmation Using Surrogate Modelling in Industry
Most manufacturing processes suffer from small deviations, which may lead to rejections of some products due to malfunctioning. In this context, malfunctioning is commonly understood
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