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Scientific paper - Original scientific paper
Predviđanje svojstava betona od recikliranih agregata
Građevinar, 69 (2017), 5; 347-357. https://doi.org/10.14256/JCE.1867.2016
Miličević, Ivana; Kalman Šipoš, Tanja

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Miličević, I. & Kalman Šipoš, T. (2017). Predviđanje svojstava betona od recikliranih agregata. Građevinar, 69. (5), 347-357. doi: 10.14256/JCE.1867.2016

Miličević, Ivana and Tanja Kalman Šipoš. "Predviđanje svojstava betona od recikliranih agregata." Građevinar, vol. 69, no. 5, 2017, pp. 347-357. https://doi.org/10.14256/JCE.1867.2016

Miličević, Ivana and Tanja Kalman Šipoš. "Predviđanje svojstava betona od recikliranih agregata." Građevinar 69, no. 5 (2017): 347-357. https://doi.org/10.14256/JCE.1867.2016

Miličević, I. and Kalman Šipoš, T. (2017) 'Predviđanje svojstava betona od recikliranih agregata', Građevinar, 69(5), pp. 347-357. doi: 10.14256/JCE.1867.2016

Miličević I, Kalman Šipoš T. Predviđanje svojstava betona od recikliranih agregata. Građevinar [Internet]. 2017 June [cited 2024 November 29];69(5):347-357. doi: 10.14256/JCE.1867.2016

I. Miličević and T. Kalman Šipoš, "Predviđanje svojstava betona od recikliranih agregata", Građevinar, vol. 69, no. 5, pp. 347-357, June 2017. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:133:845957. [Accessed: 29 November 2024]

Metadata
Title (croatian)Predviđanje svojstava betona od recikliranih agregata
Title (english)Prediction of properties of recycled aggregate concrete
Title (german)Vorhersage der eigenschaften von recyclingbeton
AuthorIvana Miličević
AuthorTanja Kalman Šipoš
Author's institutionJosip Juraj Strossmayer University of Osijek
Faculty of Civil Engineering and Architecture Osijek
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Civil Engineering
Abstract (croatian)
Upotreba recikliranih materijala kao zamjene prirodnom agregatu u betonu značajna je iz ekološki prihvatljivog aspekta njegove ponovne upotrebe. Veza između komponenti betona i njegovih svojstava ne može biti prikazana samo na osnovi matematičkih formula. Prema tome, primijenjene su umjetne neuronske mreže i regresijska analiza eksperimentalnih rezultata postignutih planiranjem eksperimenta. Dokazano je da obje primijenjene tehnike omogućuju visoku pouzdanost za modeliranje svojstava betona na osnovi njegovih komponenti.
Abstract (english)
Use of recycled materials as replacement for natural aggregate in concrete is important considering the environmentally beneficial aspect of its re-use. Relations between concrete components and concrete properties cannot be presented based on mathematical formulas only. Consequently, artificial neural networks and regression techniques were applied to analyse experimental results obtained according to previous experimental design. It was established that both techniques enable highly reliable modelling of concrete properties based on its components.
Abstract (german)
Die Anwendung von recyceltem Material als Ersatz natürlicher Gesteinskörnung für Beton ist aufgrund des ökologisch akzeptablen Aspekts der Wiederverwertung bedeutend. Der Zusammenhang zwischen den Betonkomponenten und seinen Eigenschaften kann nicht ausschließlich mittels mathematischer Formeln dargestellt werden. Daher wurden künstliche neuronale Netze und eine Regressionsanalyse experimenteller Resultate im Bezug zur Planung des Experiments angewandt. Es wurde bewiesen, dass beide eingesetzten Techniken eine hohe Zuverlässigkeit bei der Modellierung von Betoneigenschaften aufgrund seiner Komponenten aufweisen.
Keywords (croatian)
Keywords (english)
Keywords (german)
Languagecroatian
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review
Publication versionPublished version
Journal titleGrađevinar
Numberingvol. 69, no. 5, pp. 347-357
p-ISSN0350-2465
e-ISSN1333-9095
DOIhttps://doi.org/10.14256/JCE.1867.2016
URN:NBNurn:nbn:hr:133:845957
Publication2017-06
Document URLhttps://hrcak.srce.hr/183243
Type of resourceText
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2018-02-12 09:42:58