Pregled bibliografske jedinice broj: 1136824
Reducing computational time for FEM post- processing through the use of feedforward neural networks
Reducing computational time for FEM post- processing through the use of feedforward neural networks // Book of Extended Abstracts of the 6th ECCOMAS Young Investigators Conference
Valencia, Španjolska, 2022. str. 397-402 doi:10.4995/YIC2021.2021.12473 (predavanje, recenziran, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1136824 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Reducing computational time for FEM post-
processing through the use of feedforward
neural networks
Autori
Zlatić, Martin ; Čanađija, Marko
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Book of Extended Abstracts of the 6th ECCOMAS Young Investigators Conference
/ - , 2022, 397-402
Skup
6th ECCOMAS Young Investigators Conference
Mjesto i datum
Valencia, Španjolska, 07.07.2021. - 09.07.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Recenziran
Ključne riječi
Machine Learning, FEM, Postprocessing
Sažetak
With the recent surge in neural network usage, machine learning libraries have become more convenient to use and implement. In this paper the possibility of using neural networks in order to faster process displacements obtained from nite element calculation and replace existing post- processing procedures is investigated. The method is implemented on 2D membrane nite elements for their relative simplicity. A speed up is observed in comparison to traditional methods of post- processing. Possible further applications of this method are also presented in this paper.
Izvorni jezik
Engleski
Znanstvena područja
Temeljne tehničke znanosti
POVEZANOST RADA
Projekti:
HRZZ-IP-2019-04-4703 - Nelokalni mehanički modeli nanogreda (nonNano) (Čanađija, Marko, HRZZ - 2019-04) ( CroRIS)
Ustanove:
Tehnički fakultet, Rijeka
