Large-scale seismic assessment of RC buildings through rapid visual screening

被引:10
|
作者
Ahmed, Shaheryar [1 ]
Abarca, Andres [1 ]
Perrone, Daniele [2 ]
Monteiro, Ricardo [1 ]
机构
[1] Univ Sch Adv Studies IUSS Pavia, Pavia, Italy
[2] Univ Salento, Lecce, Italy
关键词
Seismic vulnerability; RC buildings; Rapid visual screening; Northern Algeria; Machine learning; RISK-ASSESSMENT; FRAGILITY;
D O I
10.1016/j.ijdrr.2022.103219
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Rapid urban growth, particularly in developing countries, is often accompanied by unplanned and highly vulnerable settlements which could lead to high seismic risk. This problem becomes even more pronounced when such developing countries are located in seismic prone regions, which, without a well-enforced seismic code, face high probability of major human and economic losses following a seismic event. With this in mind, large-scale rapid visual screening (RVS) procedures to perform seismic vulnerability assessment are of paramount importance to, at least, obtain a preliminary estimate of the risk to which buildings of a certain region are exposed to. RVS methods generally provide a seismic risk index based on the site hazard, the structural vulner-ability and the exposure. This paper presents one of many available RVS procedures, applied and assessed for large-scale seismic vulnerability mapping of a case-study province in Northern Algeria. Based on data collected during ad-hoc field surveys, the index-based selected RVS methodology was adapted to the reinforced concrete (RC) portion of the building portfolio, featuring over 2900 buildings, to estimate its seismic vulnerability. Taking advantage of a large amount of available data, a parametric study was then performed to understand the effect of the individual variables used in the RVS method on the vulnerability indices of the different buildings. The consistency of the method, as evi-denced by the results found across different building stock typologies, was also investigated to confirm the soundness of RVS approaches in large-scale assessments. Furthermore, in specific for the case-study region, the outcome of this study is extremely useful for preliminary identification of buildings (or building classes) more prone to earthquake damage and to assist decision-makers in planning seismic risk reduction strategies.
引用
收藏
页数:17
相关论文
共 50 条
  • [21] Large-scale seismic damage scenario assessment of precast buildings after the May 2012 Emilia earthquake
    Pratico, Lucia
    Bovo, Marco
    Buratti, Nicola
    Savoia, Marco
    BULLETIN OF EARTHQUAKE ENGINEERING, 2022, 20 (15) : 8411 - 8444
  • [22] Large-scale seismic damage scenario assessment of precast buildings after the May 2012 Emilia earthquake
    Lucia Praticò
    Marco Bovo
    Nicola Buratti
    Marco Savoia
    Bulletin of Earthquake Engineering, 2022, 20 : 8411 - 8444
  • [23] Dual Approach to Large-Scale Seismic Vulnerability Assessment of Churches Through Representative Archetypes
    Cianchino, Giorgia
    Masciotta, Maria Giovanna
    De Matteis, Gianfranco
    Brando, Giuseppe
    HERITAGE, 2024, 7 (12): : 6998 - 7030
  • [24] An Example-Guide for Rapid Seismic Assessment and FRP Strengthening of Substandard RC Buildings
    Tastani, Sousana
    Thermou, Georgia
    APPLIED SCIENCES-BASEL, 2022, 12 (24):
  • [25] Rapid assessment for seismic vulnerability of low and medium rise infilled RC frame buildings
    Hanan Al-Nimry
    Musa Resheidat
    Saddam Qeran
    Earthquake Engineering and Engineering Vibration, 2015, 14 : 275 - 293
  • [26] Rapid assessment for seismic vulnerability of low and medium rise infilled RC frame buildings
    Hanan Al-Nimry
    Musa Resheidat
    Saddam Qeran
    EarthquakeEngineeringandEngineeringVibration, 2015, 14 (02) : 275 - 293
  • [27] Rapid assessment for seismic vulnerability of low and medium rise infilled RC frame buildings
    Al-Nimry, Hanan
    Resheidat, Musa
    Qeran, Saddam
    EARTHQUAKE ENGINEERING AND ENGINEERING VIBRATION, 2015, 14 (02) : 275 - 293
  • [28] Neural networks for the rapid seismic assessment of existing moment-frame RC buildings
    Stefanini, Lorenzo
    Badini, Lorenzo
    Mochi, Giovanni
    Predari, Giorgia
    Ferrante, Annarita
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2022, 67
  • [29] Development of a Fuzzy Inference System Based Rapid Visual Screening Method for Seismic Assessment of Buildings Presented on a Case Study of URM Buildings
    Bektas, Nurullah
    Lilik, Ferenc
    Kegyes-Brassai, Orsolya
    SUSTAINABILITY, 2022, 14 (23)
  • [30] Rapid screening method for the determination of seismic vulnerability assessment of RC building stocks
    Onur Coskun
    Alper Aldemir
    Mustafa Sahmaran
    Bulletin of Earthquake Engineering, 2020, 18 : 1401 - 1416