Miluccio, Giacomo;
Gentile, Roberto;
Galasso, Carmine;
Parisi, Fulvio;
(2022)
Performance Assessment of Buildings Subjected to Earthquake-Induced Landslides through Gaussian Process Regression.
In:
13th International Conference on Structural Safety & Reliability Program.
International Association for Structural Safety & Reliability: Shanghai, China.
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Abstract
Earthquake-induced landslides can significantly increase structural damage to buildings located on slopes with respect to the damage due to ground shaking only. Accordingly, multi-hazard vulnerability modelling of structures should account for the cumulative damage due to earthquake-induced ground motions and landslide-related actions. This paper presents a numerical procedure based on surrogate modelling for the computationally efficient prediction of structural response to earthquake shaking and resulting landslides if any. Specifically, discriminant classifiers and Gaussian process regression are used to develop metamodels mapping the main structural characteristics (e.g., geometric and material properties) to engineering demand parameters of interest. The proposed procedure is applied to an archetype reinforced concrete frame building designed only for gravity loads and located at the toe of a slope. Analysis results show that surrogate models allow a quick yet accurate prediction of structural performance.
Type: | Proceedings paper |
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Title: | Performance Assessment of Buildings Subjected to Earthquake-Induced Landslides through Gaussian Process Regression |
Event: | 13th International Conference on Structural Safety & Reliability (ICOSSAR 2021-22) |
Location: | Shanghai, China |
Open access status: | An open access version is available from UCL Discovery |
Publisher version: | http://www.icossar2021.org/Assets/userfiles/sys_eb... |
Language: | English |
Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | buildings; earthquakes; landslides; Gaussian process regression; multi-hazard performance assessment. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Inst for Risk and Disaster Reduction |
URI: | https://discovery.ucl.ac.uk/id/eprint/10180482 |
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