| | SLO | ENG | Piškotki in zasebnost

Večja pisava | Manjša pisava

Izpis gradiva Pomoč

Naslov:Additive manufacturing of lightweight lattice structure gears designed by topology optimization and surrogate modeling
Avtorji:ID Ramadani, Riad (Avtor)
ID Günay, Elif Elçin (Avtor)
ID Pal, Snehashis (Avtor)
ID Predan, Jožef (Avtor)
ID Kegl, Marko (Avtor)
ID Drstvenšek, Igor (Avtor)
ID Okudan Kremer, Gül (Avtor)
Datoteke:URL https://link.springer.com/article/10.1007/s00170-026-18652-y
 
Jezik:Angleški jezik
Vrsta gradiva:Neznano
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FS - Fakulteta za strojništvo
Opis:Lattice structures have been widely used due to their potential in lightweight structural applications. In this study, a new approach for the design and optimization of a lattice structure fabricated by additive manufacturing (AM) was proposed to decrease volume under acceptable stress levels. A solid gear body was converted into a lightweight lattice structure and optimized employing a parametric design approach and topology optimization. Initially, Artificial Neural Network (ANN) and Kriging surrogate models were employed to explain the relationship between unit cell parameters, namely strut diameter and cell dimension, and stress levels and volume. Subsequently, the ANN model exhibiting the lower prediction error was employed in conjunction with a genetic algorithm (GA) to determine the optimal unit cell parameters. Using these optimal cell parameters as initial design parameters for the gear, topology optimization was then applied to further reduce stress concentrations. The final gear was fabricated from a mixture of powders of AlSi10Mg and NiCrMo using a laser powder bed fusion AM process. The AlSi10Mg matrix composite was reinforced in-situ with 2.5 wt% NiCrMo particles. Following this approach for lattice structure optimization, the total mass of a gear was reduced by 46.3%, while providing proper stiffness.
Ključne besede:lattice structure design, gear body, topology optimization, artificial neural network, additive manufacturing
Datum objave:01.07.2026
Leto izida:2026
Št. strani:[15] str.
Številčenje:Vol. 145, iss. 7/8
PID:20.500.12556/DKUM-99281 Novo okno
UDK:658.5:004.8
COBISS.SI-ID:286770179 Novo okno
DOI:10.1007/s00170-026-18652-y Novo okno
ISSN pri članku:1433-3015
Datum objave v DKUM:11.08.2026
Število ogledov:333
Število prenosov:4
Metapodatki:XML DC-XML DC-RDF
Področja:Ostalo
:
Kopiraj citat
  
Skupna ocena:(0 glasov)
Vaša ocena:Ocenjevanje je dovoljeno samo prijavljenim uporabnikom.
Objavi na:Bookmark and Share



Postavite miškin kazalec na naslov za izpis povzetka. Klik na naslov izpiše podrobnosti ali sproži prenos.

Gradivo je del revije

Naslov:The international journal of advanced manufacturing technology
Skrajšan naslov:Int. j. adv. manuf. technol.
Založnik:Springer
ISSN:1433-3015
COBISS.SI-ID:513743129 Novo okno

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:zasnova rešetkaste strukture, telo zobnika, optimizacija topologije, umetne nevronske mreže, dodajalne tehnologije


Komentarji

Dodaj komentar

Za komentiranje se morate prijaviti.

Komentarji (0)
0 - 0 / 0
 
Ni komentarjev!

Nazaj
Logotipi partnerjev Univerza v Mariboru Univerza v Ljubljani Univerza na Primorskem Univerza v Novi Gorici