Results and models for Novel high frequency components with non-conventional shape employing smooth geometry deformation of 3D solid with FFD - Open Research Data - MOST Wiedzy

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Results and models for Novel high frequency components with non-conventional shape employing smooth geometry deformation of 3D solid with FFD

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Opis

The project aims to investigate the possibility of developing and manufacturing novel high frequency devices having non-standard geometries, allowing for improved electromagnetic performance over what is achievable with currently available design tools. The non-conventional geometry will be obtained by employing the free-form shape deformation technique and 3D printing technology.
The proposed application of the shape deformation technique in the process of designing microwave components will allow to overcome the existing limitations of 3D modelling available in commercial electromagnetic field simulators.
The use of free-form deformation method will open the possibility of modeling an almost unlimited space of unconventional shapes with smooth profiles, as well as their easy modification, giving the designer additional degrees of freedom in the design process. Such an approach opens up new possibilities for the development of completely new devices. The resulting structures will have smooth surfaces, eliminating the presence of sharp edges, which is preferred when the device is manufactured by 3D printing. Such approach will allow for manufacturing devices with improved electrical parameters, which are not achievable by conventional modelling tools.

The following dataset contains 3D models of the designed microwave filters presented in listed peer reviewed publications in STL file format, as well as measurement results (S-parameters response) of these devices in S2P format. 

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Dataset_novel_passive_components_NCN_2022_2023.zip
15.4 MB, S3 ETag 53486061c42260142bfab18d7b84fb55-1, pobrań: 15
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hexmd5(md5(part1)+md5(part2)+...)-{parts_count} gdzie pojedyncza część pliku jest wielkości 512 MB

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https://github.com/antespi/s3md5
pobierz plik Dataset_novel_passive_components_NCN_2022_2023.zip

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Licencja:
Creative Commons: by 4.0 otwiera się w nowej karcie
CC BY
Uznanie autorstwa

Informacje szczegółowe

Rok publikacji:
2023
Data zatwierdzenia:
2023-03-08
Data wytworzenia:
2022
Język danych badawczych:
angielski
Dyscypliny:
  • automatyka, elektronika, elektrotechnika i technologie kosmiczne (Dziedzina nauk inżynieryjno-technicznych)
DOI:
Identyfikator DOI 10.34808/5vgj-pf89 otwiera się w nowej karcie
Finansowanie:
Weryfikacja:
Politechnika Gdańska

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