Pregled bibliografske jedinice broj: 477305
Genetic algorithm based optimisation of conveyor belt material cross section area
Genetic algorithm based optimisation of conveyor belt material cross section area // Tehnički vjesnik : znanstveno-stručni časopis tehničkih fakulteta Sveučilišta u Osijeku, 17 (2010), 2; 137-143 (međunarodna recenzija, članak, znanstveni)
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Naslov
Genetic algorithm based optimisation of conveyor belt material cross section area
Autori
Vrcan, Željko ; Lovrin, Neven
Izvornik
Tehnički vjesnik : znanstveno-stručni časopis tehničkih fakulteta Sveučilišta u Osijeku (1330-3651) 17
(2010), 2;
137-143
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
belt conveyor; conveyor belt; genetic algorithm; load capacity; optimisation
Sažetak
Belt conveyors are used to transport large quantities of bulk material quickly and economically over short to medium distances, e.g. for transfer from the extraction point to a processing station or shipment point. The load capacity of a belt conveyor depends on several factors, such as the trough cross section of the conveyor belt, belt speed, material density and material angle of surcharge. The load capacity of belt conveyors is mostly determined by the trough cross section, so cross sections of commercially available troughs have been compared to cross sections of matching roller layout, but optimised via a genetic algorithm. A comparison has also been made with deep semi-circular troughs, due to a significant increase in material cross section when compared to flat, v-shaped, trapezoidal and polygonal troughs.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Ustanove:
Tehnički fakultet, Rijeka
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
Uključenost u ostale bibliografske baze podataka::
- Compendex (EI Village)
- EMBASE (Excerpta Medica)
- INSPEC
- Scopus
- GeoAbstracts
- Cambridge Scientific Abstracts
- Elsevier Biobase
- Elsevier GeoAbstracts
- PaperChem