Naslov
A machine learning approach to the seismic fragility assessment of buildings

Autori
Rocchi, Alessandro ; Chiozzi, Andrea ; Nale, Marco ; Nikolic, Zeljana ; Benvenuti, Elena

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
ECCOMAS MSF 2021 - 5th International Conference on Multi-scale Computational Methods for Solids and Fluids / Ibrahimbegović, Adnan ; Nikolić, Mijo - Split : Građevinski fakultet Univerziteta u Sarajevu, 2021, 71-73

ISBN
978-9958-638-66-4

Skup
5th International Conference on Multi-Scale Computational Methods for Solids and Fluids (ECCOMAS MSF 2021)

Mjesto i datum
Split, Hrvatska, 30.06.2021. - 02.07.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Performance-Based Earthquake Engineering ; Machine learning ; Seismic fragility assessment ; Buildings

Sažetak
In the context of Performance-Based Earthquake Engineering, an intensity measure provides a link between the probabilistic seismic hazard analysis and the probabilistic structural response analysis. The purpose of this study is to develop a structural damage classifier and improve current prediction on the basis of a given intensity measure and different supervised machine learning algorithms: Support-Vector Machine, Logistic Regression and Random Forest. In particular, the efficiency of four different IMs for estimating the seismic response of three different kind of buildings is evaluated, namely peak ground acceleration, spectral acceleration evaluated at the principal period, average spectral acceleration and filtered incremental velocity. The classifier will be able to predict the post- earthquake damage state, given the geometry of the building and the intensity of the ground motion input. In particular, the purpose of this classifier is to accelerate post- earthquake damage evaluation of critical buildings. This will allow faster recovery time and decrease financial losses expected from downtime and repair. A focus is made on three different buildings typologies that can be used to represent the majority of the building stock in the city of Ferrara (Italy).

Izvorni jezik
Engleski

Znanstvena područja
Građevinarstvo, Temeljne tehničke znanosti

POVEZANOST RADA