Probabilistic Loss Assessment for the Typology of Non-Ductile Reinforced Concrete Structures with Flat Slabs, Embedded Beams, and Unreinforced Infill Masonry

Quito, the capital of Ecuador, a development pole, has experienced a population growth of 9% in the last five years. The structural system commonly chosen for housing is reinforced concrete frames with flat slabs, embedded beams, and masonry infill. This typology covers approximately 60% of the residential buildings in the city. Adding to the site’s seismic hazard, this fact results in a city with a high seismic risk. The research presented here is carried out within a probabilistic framework to determine the economic consequences of the main structural typology in the city. The methodology defines the seismic hazard by scaling a database of 200 records to the design spectrum. It models the typology to capture the variability between structures with a solid parametric study. Each capacity curve is analyzed through a nonlinear time history analysis using an equivalent one-degree-of-freedom system. The results show an average annual loss ratio of 0.16%. This metric indicates the vulnerability of the typology and the high repair costs of buildings that will be observed in case of an earthquake. The practical implications of these findings are significant as they contribute to urban planning and policy decisions. Finally, it is observed that the probabilistic method used efficiently generates fragility and vulnerability curves, saving computational time and obtaining expected results.

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Publication Details

Journal
Buildings
Published
2024-10-03
DOI
https://doi.org/10.3390/buildings14103158
Primary Topic
Structural Behavior of Reinforced Concrete
Type
article
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article

Probabilistic Loss Assessment for the Typology of Non-Ductile Reinforced Concrete Structures with Flat Slabs, Embedded Beams, and Unreinforced Infill Masonry

Ana Gabriela Haro, José Poveda, Mauricio Guamán-Naranjo
Buildings
Structural Behavior of Reinforced Concrete
article

Probabilistic Loss Assessment for the Typology of Non-Ductile Reinforced Concrete Structures with Flat Slabs, Embedded Beams, and Unreinforced Infill Masonry

Ana Gabriela Haro, José Poveda, Mauricio Guamán-Naranjo
article en

Abstract

Quito, the capital of Ecuador, a development pole, has experienced a population growth of 9% in the last five years. The structural system commonly chosen for housing is reinforced concrete frames with flat slabs, embedded beams, and masonry infill. This typology covers approximately 60% of the residential buildings in the city. Adding to the site’s seismic hazard, this fact results in a city with a high seismic risk. The research presented here is carried out within a probabilistic framework to determine the economic consequences of the main structural typology in the city. The methodology defines the seismic hazard by scaling a database of 200 records to the design spectrum. It models the typology to capture the variability between structures with a solid parametric study. Each capacity curve is analyzed through a nonlinear time history analysis using an equivalent one-degree-of-freedom system. The results show an average annual loss ratio of 0.16%. This metric indicates the vulnerability of the typology and the high repair costs of buildings that will be observed in case of an earthquake. The practical implications of these findings are significant as they contribute to urban planning and policy decisions. Finally, it is observed that the probabilistic method used efficiently generates fragility and vulnerability curves, saving computational time and obtaining expected results.

BuildingsVol. 14(10)
Universidad de las Fuerzas Armadas ESPE (EC), University of Pavia (IT)
Sustainable cities and communities
Openalex Percentile: Top 83%
Structural Behavior of Reinforced Concrete
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Probabilistic Loss Assessment for the Typology of Non-Ductile Reinforced Concrete Structures with Flat Slabs, Embedded Beams, and Unreinforced Infill Masonry — Ana Gabriela Haro, José Poveda, et al. · Buildings (2024) | TGRS Research Map | TGRS