Pregled bibliografske jedinice broj: 203617
Use of neural network to evaluate rebar corrosion in continental environment
Use of neural network to evaluate rebar corrosion in continental environment // International Conference on Construction Materials : Performance, Innovations and Structural Implications : CONMAT'05 : Book of Abstracts / Banthia, N ; Uomoto, T. ; Bentur, A ; Shah, S. P. (ur.).
Vancouver: The University of British Columbia, 2005. str. 268-268 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 203617 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Use of neural network to evaluate rebar corrosion in continental environment
Autori
Ukrainczyk, Neven ; Ukrainczyk, Velimir
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
International Conference on Construction Materials : Performance, Innovations and Structural Implications : CONMAT'05 : Book of Abstracts
/ Banthia, N ; Uomoto, T. ; Bentur, A ; Shah, S. P. - Vancouver : The University of British Columbia, 2005, 268-268
Skup
International Conference on Construction Materials : Performance, Innovations and Structural Implications (3 ; 2005)
Mjesto i datum
Vancouver, Kanada, 22.08.2005. - 24.08.2005
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
rebar corrosion; continental climate; damages categorization; simulation; classification artificial neural network
Sažetak
Data on the effects of the structure and properties of concrete onto the degree of damage caused by steel corrosion have been gathered on seven concrete bridge structures in Croatian moderate continental climate. The damages were classified into five categories based on the type of necessary remedial works. The artificial neural network for feature categorization was used as tool for classification of damage and prediciton of damage degree. It was demonstrated that the developed model could predict degree of damage confidently within the observed period. The model is able to recognize and evaluate the effect of individual parameters on the damages. Interactions and sensitivites among parameters were investigated. The developed model could be useful for planning the maintenance of investigated strucutres and design of remedial works.
Izvorni jezik
Engleski
Znanstvena područja
Građevinarstvo, Kemijsko inženjerstvo
Napomena
Puni tekst rada objavljen na CD-u.
POVEZANOST RADA
Ustanove:
Građevinski fakultet, Zagreb,
Fakultet kemijskog inženjerstva i tehnologije, Zagreb