prikaz prve stranice dokumenta Prediction of the Seismic Response of Multi- Storey Multi-Bay Masonry Infilled Frames Using Artificial Neural Networks and a Bilinear Approximation
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Prediction of the Seismic Response of Multi- Storey Multi-Bay Masonry Infilled Frames Using Artificial Neural Networks and a Bilinear Approximation
Buildings, 9 (2019), 5; 121. https://doi.org/10.3390/buildings9050121
Kalman Šipoš, Tanja; Strukar, Kristina

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Kalman Šipoš, T. i Strukar, K. (2019). Prediction of the Seismic Response of Multi- Storey Multi-Bay Masonry Infilled Frames Using Artificial Neural Networks and a Bilinear Approximation. Buildings, 9. (5). doi: 10.3390/buildings9050121

Kalman Šipoš, Tanja i Kristina Strukar. "Prediction of the Seismic Response of Multi- Storey Multi-Bay Masonry Infilled Frames Using Artificial Neural Networks and a Bilinear Approximation." Buildings, vol. 9, br. 5, 2019. https://doi.org/10.3390/buildings9050121

Kalman Šipoš, Tanja i Kristina Strukar. "Prediction of the Seismic Response of Multi- Storey Multi-Bay Masonry Infilled Frames Using Artificial Neural Networks and a Bilinear Approximation." Buildings 9, br. 5 (2019). https://doi.org/10.3390/buildings9050121

Kalman Šipoš, T. i Strukar, K. (2019) 'Prediction of the Seismic Response of Multi- Storey Multi-Bay Masonry Infilled Frames Using Artificial Neural Networks and a Bilinear Approximation', Buildings, 9(5). doi: 10.3390/buildings9050121

Kalman Šipoš T, Strukar K. Prediction of the Seismic Response of Multi- Storey Multi-Bay Masonry Infilled Frames Using Artificial Neural Networks and a Bilinear Approximation. Buildings [Internet]. 2019. [pristupljeno 27.12.2024.];9(5). doi: 10.3390/buildings9050121

T. Kalman Šipoš i K. Strukar, "Prediction of the Seismic Response of Multi- Storey Multi-Bay Masonry Infilled Frames Using Artificial Neural Networks and a Bilinear Approximation", Buildings, vol. 9, br. 5, 2019. [Online]. Dostupno na: https://urn.nsk.hr/urn:nbn:hr:133:773124. [Citirano: 27.12.2024.]

Za citiranje koristite ovu mrežnu adresu: https://urn.nsk.hr/urn:nbn:hr:133:773124
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Podaci o radu
Naslov (engleski)Prediction of the Seismic Response of Multi- Storey Multi-Bay Masonry Infilled Frames Using Artificial Neural Networks and a Bilinear Approximation
AutorTanja Kalman Šipoš
AutorKristina Strukar
Autorova ustanovaSveučilište Josipa Jurja Strossmayera u Osijeku
Građevinski i arhitektonski fakultet Osijek
Znanstveno / umjetničko
područje, polje i grana		TEHNIČKE ZNANOSTI
Građevinarstvo
Sažetak (engleski)
In order to test the reliability of neural networks for the prediction of the behaviour of multi-storey multi-bay infilled frames, neural network processing was done on an experimental database of one-storey one-bay reinforced- concrete (RC) frames with masonry infills. From the obtained results it is demonstrated that they are acceptable for the prediction of base shear (BS) and inter-storey drift ratios (IDR) in characteristic points of the primary curve of infilled frame behaviour under seismic loads. The results obtained on one-storey one-bay infilled frames was extended to multi-bay infilled frames by evaluating and comparing numerical finite element modelling(FEM) modelling and neural network results with suggested approximating equations for the definition of bilinear capacity by defined BS and IDRs. The main goal of this paper is to offer an interpretation of the behaviour of multi-storey multi-bay masonry infilled frames according to a bilinear capacity curve, and to present the infilled frame’s response according to the contributions of frame and infill. The presented methodology is validated by experimental results from multi-storey multi-bay masonry infilled frames.
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Izvorni znanstveni rad
Status objaveObjavljen
Vrsta recenzijeRecenziran - međunarodna recenzija
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov časopisaBuildings
Brojčani podacivol. 9, br. 5, 121
p-ISSN2075-5309
DOIhttps://doi.org/10.3390/buildings9050121
URN:NBNurn:nbn:hr:133:773124
Datum objave publikacije2019
URL dokumentahttps://www.mdpi.com/2075-5309/9/5/121
Vrsta resursaTekst
Prava pristupaOtvoreni pristup
Uvjeti korištenjaIkona licence Imenovanje 4.0 međunarodna (CC BY 4.0)
Datum i vrijeme pohrane2024-12-03 09:15:26