Pregled bibliografske jedinice broj: 1006192
Reliability analysis with Metamodel Line Sampling
Reliability analysis with Metamodel Line Sampling // Structural safety, 60 (2016), 1-15 doi:10.1016/j.strusafe.2015.12.005 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1006192 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Reliability analysis with Metamodel Line Sampling
Autori
Đepina, Ivan ; Le, Thi Minh Hue ; Fenton, Gordon ; Eiksund, Gudmund
Izvornik
Structural safety (0167-4730) 60
(2016);
1-15
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
metamodel ; reliability ; line sampling ; kriging ; monopile ; offshore
Sažetak
This paper presents an approach for reliability analysis of engineering structures, referred to as Metamodel Line Sampling (MLS). The approach utilizes a metamodel of the performance function, within the framework of the Line Sampling method, to reduce computational demands associated with the reliability analysis of engineering structures. Given a metamodel of the performance function, the failure probability is estimated as a product of a metamodel-based failure probability and a correction coefficient. The correction coefficient accounts for the error in the metamodel estimate of failure probability introduced by the replacement of the performance function with a metamodel. Computational efficiency and accuracy of the MLS approach are evaluated with the Kriging metamodel on analytical reliability problems and a practical reliability problem of a monopile foundation for offshore wind turbine. The MLS approach demonstrated efficient performance in low to medium-dimensional reliability problems.
Izvorni jezik
Engleski
Znanstvena područja
Građevinarstvo
POVEZANOST RADA
Ustanove:
Fakultet građevinarstva, arhitekture i geodezije, Split
Profili:
Ivan Đepina
(autor)
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