Pregled bibliografske jedinice broj: 379711
Genetic algorithm in material model parameters’ identification for low-cycle fatigue
Genetic algorithm in material model parameters’ identification for low-cycle fatigue // Computational Materials Science, 45 (2009), 2; 505-510 doi:10.1016/j.commatsci.2008.11.012 (međunarodna recenzija, članak, znanstveni)
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Naslov
Genetic algorithm in material model parameters’ identification for low-cycle fatigue
Autori
Franulović, Marina ; Basan, Robert ; Prebil, Ivan
Izvornik
Computational Materials Science (0927-0256) 45
(2009), 2;
505-510
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Inelastic constitutive material model; Material parameter identification; Genetic algorithm; Numerical optimization; Computer modelling; Computer simulation
Sažetak
The material model presented in this paper describes elasto– plastic behaviour of the material under a cyclic load application. It takes into account damage occurrence and accumulation in the material and it’ s relation to isotropic and kinematic hardening or softening. The material constitutive model is highly non-linear and therefore it’ s parameter identification requires complex numerical procedure, such as genetic algorithm. Because of it’ s complexity, the unique genetic operators’ routines in genetic algorithm calculation procedure are developed to make possible fast and reliable convergence to the results. These routines are incorporated in developed software solution. The calculation resulted in identification of material parameters that are validated in comparing material response of numerical solution with experimental data.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Projekti:
069-0692195-1796 - Materijali, trajnost i nosivost suvremenih zupčastih prijenosnika (Križan, Božidar, MZOS ) ( CroRIS)
Ustanove:
Tehnički fakultet, Rijeka
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus