Pregled bibliografske jedinice broj: 1199336
Robust feasibility verification and region inner- point detection algorithms for geometric shape objects applied to electric machine optimization workflow
Robust feasibility verification and region inner- point detection algorithms for geometric shape objects applied to electric machine optimization workflow // Structural and multidisciplinary optimization, 65 (2022), 175, 11 doi:10.1007/s00158-022-03263-4 (međunarodna recenzija, članak, znanstveni)
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Naslov
Robust feasibility verification and region inner-
point detection
algorithms for geometric shape objects applied to
electric machine
optimization workflow
(Robust feasibility verification and region inner-
point
detection algorithms for geometric shape objects
applied to
electric machine optimization workflow)
Autori
Ban, Branko ; Stipetić, Stjepan
Izvornik
Structural and multidisciplinary optimization (1615-147X) 65
(2022);
175, 11
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Electric machine, Design feasibility, Robust, Material, Region, Shape object
Sažetak
In most cases, the search for the optimal design of an electrical machine is closely related to its 2D radial cross section. When optimizing a 2D cross section, special attention must be paid to the geometry and to the definition of the parameters along with their boundaries. Even if properly bounded, complex geometries generated by optimization algorithms can lead to geometrically infeasible candidates. These cannot be manufactured because they contain generally undesirable geometric relationships between air, magnets, and steel. Different commercial and open- source finite element analysis (FEA) design tools treat the infeasible designs differently. The results vary from simulation stop to successful FEA calculation of the infeasible candidate, which wastes time by producing useless data. To prevent the infeasible designs from entering the optimization competition and possibly appearing incorrectly as optimal solutions, and to reduce optimization time, it is important to capture the infeasible designs during optimization. Moreover, the FEA tool requires a precisely determined interior point to assign the material to each closed region (air, steel, epoxy, magnet...). This can be very challenging for complex geometries. To avoid creating geometry or material regions that are not valid, this paper proposes a novel robust methods for checking feasibility and determining interior points on geometric shape objects. In this paper, the proposed method is applied to the optimization of electrical machines.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus