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Pregled bibliografske jedinice broj: 477305

Genetic algorithm based optimisation of conveyor belt material cross section area


Vrcan, Željko; Lovrin, Neven
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)


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

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