Národní úložiště šedé literatury Nalezeno 2 záznamů.  Hledání trvalo 0.01 vteřin. 
Topology optimization of the line-start synchronous machines
Lolová, Iveta ; Vítek, Ondřej (oponent) ; Bárta, Jan (vedoucí práce)
The master thesis deals with topology optimization of electrical machines and line-start synchronous reluctance motor. The master thesis includes a literature review on the state of the art of topology optimizations and line-start synchronous reluctance motor. The possible concepts for characterizing the investigated design space is described. The dependency of the final normalized Gaussian network on the distribution of Gaussian functions is analysed in detail. The evaluation algorithm of a single individual is created within this thesis. The algorithm manages communication between Ansys Maxwell and software tool SyMSpace. Moreover, the algorithm leads to reducing of the computational time due to the preselection of unfeasible geometries. Furthermore, the topology optimization of LSSynRM based on the normalized Gaussian network is performed and the results are discussed.
Topology optimization of the line-start synchronous machines
Lolová, Iveta ; Vítek, Ondřej (oponent) ; Bárta, Jan (vedoucí práce)
The master thesis deals with topology optimization of electrical machines and line-start synchronous reluctance motor. The master thesis includes a literature review on the state of the art of topology optimizations and line-start synchronous reluctance motor. The possible concepts for characterizing the investigated design space is described. The dependency of the final normalized Gaussian network on the distribution of Gaussian functions is analysed in detail. The evaluation algorithm of a single individual is created within this thesis. The algorithm manages communication between Ansys Maxwell and software tool SyMSpace. Moreover, the algorithm leads to reducing of the computational time due to the preselection of unfeasible geometries. Furthermore, the topology optimization of LSSynRM based on the normalized Gaussian network is performed and the results are discussed.

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